on the potential of satellite radar interferometry for ... · on the potential of satellite radar...

“POSEIDON”

On the potential of satellite radarinterferometry for monitoring dikes of the

Netherlands

- a technical feasibility study -

17 November 2006

Frank Dentz

Lidia van Halderen

Boudewijn Possel

Sami Samiei Esfahany

Cornelis Slobbe

Tom Wortel

ii

POSEIDON, final report 17 November 2006

Version

DISTRIBUTION LIST

Person AffiliationDr.ir. R.F. Hanssen TU Delft/TutorDr.ir. M.J.P.M. Lemmens, Ir. F.J. van Leijen TU Delft/Project coaches

TU Delft/Project Management

CHANGE RECORD

Issue Date Change Record Notes Main Author Reviewed by1 September 27, 2006 Draft of the report Team Dr.ir. R.F. Hanssen

Dr.ir. M.J.P.M.LemmensIr. F.J. van Leijen

2 November 3, 2006 Final report Team Dr.ir. R.F. HanssenDr.ir. M.J.P.M.LemmensIr. F.J. van Leijen

3 November 17, 2006 Final report Team -

Version 3.0

Final Report, GSP 2006 group 1

ISSUED BY

Delft University of Technology, GeomaticsFaculty of Aerospace Engineeringc/o Mrs. M.P.M. ScholtesKluyverweg 12629 HS Delftphone: 015-2783546email: [email protected]

iii

iv CHAPTER 0. VERSION


Preface

This report is the product of nine weeks of research on the feasibility of the PS-InSAR technique for defor-mations monitoring of dikes. This research was part of the Geomatics Synthesis Project (GSP), which is apart of the 2nd year of the Geomatics master program of Delft University of Technology (DUT). The goal ofthis project is that students, in groups of 5-6 students, go through the whole chain of the geo-informationprocess to get experience in geomatic project handling. The authors of this report all started their masterstudy in September 2005, the same year as the start of the Geomatics program. In the first half of 2006, thecontours of this project became more clear. Especially, the efforts of Mr. Tiberius and Mr. Hanssen have tobe mentioned here. Due to their initiative the preparations accelerated, and the research topic was chosen.

Our thanks go out to everybody who has cooperated in establishing this report. In particular we would liketo thank Mr. Hanssen, Mr. van Leijen and Mr. Lemmens for assisting and coaching us. A significant part ofthis research was the study to what can happen with a dike in terms of deformation. This research was onlypossible due to the close collaboration with several dike experts. We want to thank Mr. van Baars en Mr.Vrijling from the faculty of Civil Engineering from DUT, Mr. Van and Mr. van Duinen from GeoDelft and Mr.Van der Meer from Fugro. Also we would like to thank Mr. Perski for his technical support with the use ofthe GRASS software, Mrs. Ketelaar for her help in the interpretation of the data and Mr. van Zwieten for hissupport in working with LaTeX. The conducted case studies were performed with the use of different datasetswe received from different organizations. Special acknowledgements go to the people who spent a lot of timein the retrieving or preparation of these datasets. Here we want to mention Mr. Ritter (Map Room of DUT),Mr. Vroonland (Adviesdienst Geo-informatie en ICT (AGI)), Mr. Landa (AGI), Mr. Boezeman (waterboardZuiderzeeland), Mr. van Duinen (GeoDelft), Mrs. Man in ’t veld (Rijkswaterstaat Noord-Holland) and Mr.Nieuwenhuis (Rijkswaterstaat Noord-Holland).

During our field trips, we received a lot of information about the local situation that gave us a lot of inspiration.Especially we would like to thank Mr. Oldenhof for his explanations during the trip to Kornwerderzand andMr. Bos for his support at Marken.

Delft, 17 November 2006

v

vi CHAPTER 0. PREFACE


Contents

Version iii

Preface v

Used abbreviations xi

Used symbols xiii

Glossary xv

Abstract xxiii

1 Introduction 1

1.1 Purpose statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Research methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.3 Boundary conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.4 Structure of the report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2 Dikes, deformation and monitoring 5

2.1 Water barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.1.1 Categories of water barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.1.2 Types of water barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.1.3 Structure of a dike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.2 Description of deformation mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.3 Legal context of dike monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.3.1 Responsibility of dike monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

2.3.2 Legal issues using InSAR for dike monitoring . . . . . . . . . . . . . . . . . . . . . . . 15

2.4 Conventional guidelines for dike monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

2.4.1 Height inspection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

2.4.2 Stability inspection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

2.5 Dike monitoring in practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.5.1 Used measurement techniques for dike monitoring . . . . . . . . . . . . . . . . . . . . 19

vii

viii CONTENTS

3 Deformation monitoring with radar interferometry 21

3.1 Introduction to InSAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

3.2 Conventional InSAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

3.2.1 Basic idea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

3.2.2 Main interferometric parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

3.2.3 Main limitations of conventional InSAR . . . . . . . . . . . . . . . . . . . . . . . . . 25

3.3 Persistent Scatterer InSAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

3.3.1 Concept of PS-InSAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

3.3.2 Main issues in interpretation of PS-InSAR results . . . . . . . . . . . . . . . . . . . . 27

4 Estimation of dike deformation parameters 31

4.1 Detection of deformation mechanisms with PS-InSAR . . . . . . . . . . . . . . . . . . . . . . 31

4.1.1 Discussion of detectability of deformation mechanisms . . . . . . . . . . . . . . . . . 31

4.1.2 Superposition of deformation mechanisms . . . . . . . . . . . . . . . . . . . . . . . . 33

4.2 Forward modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.2.1 General considerations about forward modeling . . . . . . . . . . . . . . . . . . . . . 34

4.2.2 General input parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.2.3 Modeling of deformation mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . 35

4.3 Inverse modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

5 Case study methodology 45

5.1 The choice of the case study locations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

5.2 Data gathering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

5.3 Preparation of the data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

5.3.1 Georeferencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

5.3.2 Selection of the reference point . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

5.4 Time series analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

5.5 Detection of deformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

5.6 Classification of deformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

5.7 Quality assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

5.7.1 Internal precision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

5.7.2 External precision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

5.7.3 Global Overall Model test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

5.8 Feasibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

6 Case studies 55

6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

6.2 Case study Harlingen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

6.2.1 Detection of deformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55


CONTENTS ix

6.2.2 Quality assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

6.2.3 The number of Persistent Scatterers . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

6.2.4 Summary of results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

6.3 Case study Kornwerderzand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59




6.4 Case study Marken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62


6.4.2 Time series analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

6.4.3 Estimation of deformation parameters . . . . . . . . . . . . . . . . . . . . . . . . . . 63

6.4.4 Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64



6.5 Case study Noordoostpolder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67


6.5.2 Time series analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

6.5.3 Estimation of deformation parameters . . . . . . . . . . . . . . . . . . . . . . . . . . 69

6.5.4 Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70


6.5.6 The number of Persistent Scatterers . . . . . . . . . . . . . . . . . . . . . . . . . . . 72


7 Conclusions and recommendations 75

7.1 Answer on main research question . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

7.2 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

7.2.1 Characteristics of dikes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

7.2.2 Detection and identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76


7.2.4 PS-InSAR with respect to the needs . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

7.3 Recommendations for further research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

A List of used datasets 79

B Background information Harlingen 83

C Background information Kornwerderzand 89

D Background information Marken 95

E Background information Noordoostpolder 101


x CONTENTS

F Color images 111

Bibliography 119


Used abbreviations

AGI Adviesdienst Geoinformatie en ITC (RWS department of geoinformation and ICT)AHN Actueel Hoogtebestand Nederland, current elevation model of the NetherlandsDTB Digitaal Topografisch Bestand, digital topographical filesDUT Delft University of TechnologyERS European Remote-Sensing SatelliteFliMap Fast Laser Imaging – Mapping and ProfilingGIS Geographic Information SystemGOM Global Overall Model testGPS Global Positioning SystemGPR Ground Penetrating RadarGRASS Geographic Recourses Analysis Support System, Gis-programGSP Geomatics Synthesis ProjectInSAR Interferometric SARLiDAR Light Detection And RangingLOS Line of sightMRM Multi Reflectivity MapNAP Normaal Amsterdams Peil, Dutch reference surfacePOSEIDON Potential of satellite radar interferometry for monitoring dikes of the NetherlandsPS Persistent ScattererPS-InSAR Persistent Scatterer InSARRADAR RAdio Detection And RangingRD RijksDriehoeksmeting, Dutch national gridRTK Real Time KinematicRWS RijksWaterStaat (directorate general of public works and water management)SAR Synthetic Aperture RADARTop10vector The topographic vector map on scale 1:10000

xi

xii CHAPTER 0. USED ABBREVIATIONS


Used symbols

α The distance to the dike’s length axisαh Heading of the satellite (azimuth)αha Heading of ascending orbitαhd Heading of descending orbitγ The slope of the dikeγa Azimuth of lenght axis of dikeθ Incidence angleλ Radar wavelengthλnc Non-centrality parameterσ2

v The variances of the estimated deformation ratesφatmo Phase shift due to atmosphereφdefo Phase shift due to deformationφnoise Phase shift due to noiseφscat Phase shift due to a change in the scatter characteristics of the resolution cellφtopo Topographic phaseφ∆H The differential phasedasc Observed deformation in ascending trackddesc Observed deformation in descending trackde The projection of the 3D deformation vector in east directiondinner slope The deformation magnitude of the inner slopedn The projection of the 3D deformation vector in north directiondouter slope The deformation magnitude of the outer slopedr Deformation vector in LOS componentdtop The deformation magnitude of the top of the dikedu The projection of the 3D deformation vector in up directiondx deformation perpendicular to the lenght direction of dikesdy deformation in the lenght direction of dikesdz The vertical deformationdz base The deformation of the foot of the dike in vertical directiondz foreland The uplift of the forelanddz sub The deformation of the top of the dike in z-directiondx top The deformation of the crest of the dike in horizontal directiondz top The deformation of the crest of the dike in the vertical directiondSlope The deformation vector parallel to the slopee Estimated residual vectorh The crest height of the dikek The unknown integer number of full phase cyclesl The base width of the dikex Vector of unknown parametersx BLUE of the unknown parametersti Time epoch iv The estimated deformation ratesy Vector of observationsA Model of observation equations

xiii

xiv CHAPTER 0. USED SYMBOLS

B⊥ Perpendicular baseline (distance between the satellites)D Deformation in the radar LOS∆H the topographic phase residualH Height above the reference frameHa Alternative hypothesisH0 Null hypothesisIm Identity matrix of size mQxx Variance-covariance matrix of the BLUEQyy The variance-covariance matrix of the estimated observationsQyy Variance-covariance matrix of observationsR Slant range from the master platform to the earth surfaceT q GOM test statisticY North directionX East directionZ Up direction


Glossary

Ascending (orbit) The satellite moves in upwards direction (south-north).Autonomous movement A PS-InSAR measurement that is not related to the expected defor-

mation mechanism.Boulder clay Kind of clay, more stiff and tough than normal clay.Collar mattress Geotextile with on top mats of willow branches, used for protection

against erosion of a bank (’kraagstuk ’ in Dutch).Corner reflector A retroreflector consisting of three mutually perpendicular, intersect-

ing flat surfaces, which reflects electromagnetic waves back towardsthe source

Crest height The highest point of a dike (’kruinhoogte’ in Dutch).Descending (orbit) The satellite moves in downwards direction (north-south).Dike-ring area An area fully enclosed by water barriersEmbankment Wall that protect and hold the bank (’kade’ in Dutch).High grounds Areas which are sufficiently high and broad to stop outside water.Isolated points PS points with no sidelobes and no other PSs in its surrounding.Non-primary water barriers Secondary barriers, protect against flooding by small water systems.Outlier PSs that contain only noise.Persistent Scatterer (PS) Point with constant backscatter characteristics in time.Pilings Foundation piles of a building, to protect the building against subsi-

dence (’heipalen’ in Dutch).Primary water barriers Barriers that protect against flooding by the see, large rivers or large

lakes.Protective cover Layer of stones or asphalt that protect the outer slope of a dike

against erosion.Reference point A point within the study area to which all deformation measurements

are relative.Resolution cell Radar pixel on the ground.Sidelobe Neighbouring pixel of a PS, which is also detected as PS due to the

sinc pattern of the reflected radar wave.Storage basin Water basin in which polder water is drained (’boezem’ in Dutch).tolerable water discharge Maximum amount over water that may come over the dike, which a

pumping station can handle (’overslagdebiet’ in Dutch).Water barrier Constructions that prevent the land behind it from flooding.

xv

xvi CHAPTER 0. GLOSSARY


List of Figures

1.1 Potential coastline of the Netherlands without dikes . . . . . . . . . . . . . . . . . . . . . . . 2

2.1 Primary water barriers in the Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.2 The main types of water barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.3 Schematical drawing of a dike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.4 Overview of deformation mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.5 Schematical overview of height testing procedure. . . . . . . . . . . . . . . . . . . . . . . . 16

2.6 Crumbling of basaltic stones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.7 The FliMap system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

3.1 Phase measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

3.2 Interferogram of Bam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

3.3 Different scattering resolution cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

3.4 Example of time series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

3.5 Possible deformation for buildings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.6 Autonomous movement due to settlement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

4.1 A dike body’s cross-section of the used model. . . . . . . . . . . . . . . . . . . . . . . . . . 34

4.2 Geometry of incidence angle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

4.3 Model of a deformation due to sliding. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

4.4 The decomposition of the deformation vector. . . . . . . . . . . . . . . . . . . . . . . . . . 36

4.5 Model of a deformation due to sliding of the inner slope. . . . . . . . . . . . . . . . . . . . . 36

4.6 Model of a deformation due to sliding of the outer slope of the dike. . . . . . . . . . . . . . 37

4.7 Model of a deformation due to seepage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

4.8 Model of a deformation due to sliding of the protective cover. . . . . . . . . . . . . . . . . . 37

4.9 Model of a deformation due to horizontal deformation. . . . . . . . . . . . . . . . . . . . . . 38

4.10 Model of a deformation due to settlement. . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.11 Model of a deformation due to subsidence. . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

4.12 Model of a deformation due to swelling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

4.13 The observation geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

4.14 Dike coordinate system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

xvii

xviii LIST OF FIGURES

4.15 Deformation components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

4.16 Sensitivity (standard deviation in mm) of estimated deformation parameters to the dike orien-tation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

5.1 Linear model vs. alternative models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

5.2 Other possibilities for phase unwrapping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

5.3 Decision tree for deformation detection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

5.4 Characteristics of deformation mechanisms. . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

5.5 Decision tree deformation classification: two observations . . . . . . . . . . . . . . . . . . . 51

5.6 Decision tree deformation classification: one observation . . . . . . . . . . . . . . . . . . . . 51

6.1 Deformation rate in ascending track . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

6.2 Deformation rate in descending track . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

6.3 Shifted deformation rate in ascending track . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

6.4 Shifted deformation rate in descending track . . . . . . . . . . . . . . . . . . . . . . . . . . 56

6.5 Estimated absolute subsidence due to salt mining . . . . . . . . . . . . . . . . . . . . . . . . 57

6.6 Example of time series in subsidence bowl . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

6.7 Division of dikes in straight segments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

6.8 Relation points and dike orientation w.r.t. the satellite’s orbit . . . . . . . . . . . . . . . . . . 60

6.9 Time series Marken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

6.10 PS-INSAR and leveling comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

6.11 Some time series for Case A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

6.12 Alternative time series for Case A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

6.13 Some time series for Case B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

6.14 Some time series for Case C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

6.15 Division of dikes in straight segments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

6.16 Relation points and dike orientation w.r.t. the satellite’s orbit . . . . . . . . . . . . . . . . . . 74

A.1 Example radar data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

A.2 Example top10vector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

A.3 Example DTB-wet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

A.4 Example lenght profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

A.5 Example AHN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

A.6 Example geotechnical profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

A.7 Example soil map 1:50000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

A.8 Example aerial photograph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

C.1 Location of Kornwerderzand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

C.2 Aerial overview of Kornwerderzand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

C.3 Construction of the Afsluitdijk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90


LIST OF FIGURES xix

C.4 Histogram of deformation rates of the whole dataset, ascending track . . . . . . . . . . . . . 92

C.5 Histogram of deformation rates of the whole dataset, descending track . . . . . . . . . . . . 92

C.6 Histogram of deformation rates of Kornwerderzand, ascending track . . . . . . . . . . . . . . 92

C.7 Histogram of deformation rates of Kornwerderzand, descending track . . . . . . . . . . . . . 92

D.1 Location of Marken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

D.2 Old map of Marken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

D.3 Schematical cross-section of the ring dike of Marken . . . . . . . . . . . . . . . . . . . . . . 97

D.4 northern part of ring dike Marken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

D.5 Deformation protective cover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

E.1 The Zuiderzee Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

E.2 The locations where ground improvements are carried out . . . . . . . . . . . . . . . . . . . . 102

E.3 Cross-section of the dike from 1956 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

E.4 Locations with new sheet piling in 1992 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104

E.5 The windmills near the IJsselmeer dikes in the Noordoostpolder . . . . . . . . . . . . . . . . . 108

F.1 Example of overflowing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

F.2 Example of wave overtopping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

F.3 Example of nipping ice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

F.4 Example of piping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

F.5 Example of plastic horizontal sliding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

F.6 Example of sliding of the inner slop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

F.7 Persistent Scatterers in the area of Harlingen . . . . . . . . . . . . . . . . . . . . . . . . . . 112

F.8 Radar data Harlingen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

F.9 Overall Model Test results in ascending track . . . . . . . . . . . . . . . . . . . . . . . . . . 112

F.10 Overall Model Test results in descending track . . . . . . . . . . . . . . . . . . . . . . . . . . 112

F.11 Standard deviation of residuals from linear model, ascending track . . . . . . . . . . . . . . . 112

F.12 Standard deviation of residuals from linear model, descending track . . . . . . . . . . . . . . 112

F.13 Interesting areas at Kornwerderzand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

F.14 Zoom in on area of the bridge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

F.15 Side of the bridge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

F.16 Visible deformation cracks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

F.17 Zoom in on sluice area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

F.18 Overview of the North dike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

F.19 Overall Model Test results for ascending track . . . . . . . . . . . . . . . . . . . . . . . . . 114

F.20 Overall Model Test results for descending track . . . . . . . . . . . . . . . . . . . . . . . . . 114

F.21 Standard deviation of residuals from linear model ascending track . . . . . . . . . . . . . . . 114

F.22 Standard deviation of residuals from linear model descending track . . . . . . . . . . . . . . 114

F.23 Rejected points in OMT are represented in black . . . . . . . . . . . . . . . . . . . . . . . . 114


xx LIST OF FIGURES

F.24 Accepted measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

F.25 Locations PS-InSAR points Marken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

F.26 Persistent scatter locations case study Marken . . . . . . . . . . . . . . . . . . . . . . . . . 115

F.27 GOM for ascending data Marken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

F.28 GOM for descending data Marken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

F.29 Standard deviation of residuals for ascending data Marken . . . . . . . . . . . . . . . . . . . 115

F.30 Standard deviation of residuals for descending data Marken . . . . . . . . . . . . . . . . . . . 115

F.31 Locations measurements Marken RWS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

F.32 Leveling results measurements Marken RWS . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

F.33 GPS results measurements Marken RWS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

F.34 The results of the detection step. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

F.35 The two groups of PSs for Case B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

F.36 The results of the Overall Model Test. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

F.37 Overview of datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117

F.38 Overview of radar data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117

F.39 Overview of normalized dataset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117

F.40 Normalized dataset in Matlab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117

F.41 Overview of the dikes and their deformation rates from PS-InSAR. . . . . . . . . . . . . . . 117


List of Tables

2.1 Deformation mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

4.1 Deformation mechanisms potentially detectable with PS-InSAR. . . . . . . . . . . . . . . . . 32

6.1 The number of PSs for ascending orbit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

6.2 The number of PSs for descending orbit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

6.3 Overview vertical deformation Marken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

6.4 Overview radar and leveling measurements . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

6.5 The external precision of the estimated deformation parameters . . . . . . . . . . . . . . . . 71

6.6 The number of PSs for ascending orbit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

6.7 The number of PSs for descending orbit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

B.1 Ascending data track 258 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

B.2 Descending data track 151 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85



B.3 Shift differences in meters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

B.4 Standard deviation in meters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

C.1 Shift differences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

C.2 Mean deformation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

D.1 Characteristics PS-InSAR datasets Marken. . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

D.2 Correction values georeferencing Marken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

E.1 Overview of the used datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

E.2 Ascending data track 029 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

E.3 Descending data track 151 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

E.4 Results of the georeferencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

xxi

xxii LIST OF TABLES


Abstract

Dike monitoring is an indispensable issue in countries like the Netherlands. The largest part of the Dutchpopulation lives on land reclaimed from the sea and most of the gross national product is earned in thesevulnerable areas. This implies that the continuous monitoring of dike deformation and strength with reliabletechnology is vital for the Netherlands. Satellite radar interferometry is currently recognized as an efficientmethod for the detection and monitoring of surface deformation such as subsidence.

The purpose of the POSEIDON project is to explore the potential of deformation monitoring of water barriersin the Netherlands with the satellite Interferometric Synthetic Aperture Radar (InSAR) technique.

In this report, different kinds of water barriers in the Netherlands are presented and various deformation andfailure mechanisms of dikes and their effects are studied. Also the necessity of dike monitoring is discussed,and the procedure of dike monitoring that is used in practice is described.

This report also reviews the basic concepts of the Persistent Scatter InSAR technique, the more advancedinterferometric technique that is used in this project. The main issues in the interpretation of the PS-InSARmeasurements are explained. Furthermore, it describes which kinds of deformation can be detected with thePS-InSAR technique. Inverse and forward modeling are studied to derive the deformation parameters.

To be able to decide about the technical feasibility of PS-InSAR for dike monitoring, a methodology isdeveloped. It includes detection of deformation, time-series analysis, estimation of deformation parameters,classification of detected deformation, and finally quality assessment of the results. This methodology isapplied in four different case studies in the Netherlands, namely Harlingen, Kornwerderzand, Marken and theNoordoostpolder.

The results of the case studies confirm that this technique is technically feasible for dike deformation monitoring,especially as indicator method. In particular, it shows good performance for deformation detection on dikeswhich have rock fill on their slopes.

xxiii

xxiv CHAPTER 0. ABSTRACT


Chapter 1

Introduction

The Netherlands is a country which largely consists of reclaimed land. Only because of a large amount ofinfrastructural water defense objects (dikes, dams, storm-surge barriers, etc.) it is possible to keep the areassituated below sea level dry. This can be seen in Figure 1.1 where the situation is sketched of the Netherlandswithout water barriers.

“Most of the Netherlands’ 16 million people live on land reclaimed from the sea, and 70 percent of the grossnational product is earned in these vulnerable areas. Therefore, the safety of the water barriers is of paramountimportance to maintain the balance in the Dutch society. Failure can have catastrophic humanitarian andsocio-economic consequences, as we have seen from the flooding in Zeeland (31/1/1953) when dikes breachedat 400 locations and 1800 people died. In the 1990s, climate change and increased rainfall in central Europeled to flooding of the Rhine and Meuse rivers in the Netherlands. More recently, dike failures as in Wilnis(26/8/2003), Terbregge (1/9/2003), and Stein (27/1/2004) have shown that knowledge of failure mechanismsshould be improved, and that the regular inspections of primary and secondary water barriers failed to detecthazardous areas. After August 2005, when the hurricane Katrina hit the southwestern coast of the USA andcaused breaching of the levees along New Orleans’ 17th Street and London Street canals and the city wasinundated, it created a new sense of urgency for the Netherlands to review its safety levels. ”Could thishappen here?” was a question frequently posed. Many governmental and research organizations are currentlyaddressing this question” [39].

Proper dike monitoring and maintenance can be a big step in the prevention of flooding in the Netherlands.A technique which might be appropriate for this intensive monitoring is the PS-InSAR technique. This is thetechnique whose potential will be explored in this research.

There are a number of interesting characteristics of the PS-InSAR technique which lead to the choice ofresearching the potential of this technique for monitoring of the dikes of the Netherlands. The most importantfactor is the accuracy potential, which is at sub-millimeter level due to the small wavelength of the radar. Thisaccuracy alone is not enough to make it better than existing measurement techniques; leveling has the sameor maybe even a better accuracy potential. The revisit period and the involved costs are, in combination withthe accuracy potential, unique for the PS-InSAR technique. The satellite passes over every area about oncein 35 days, so each 35 days a difference measurement can take place. The costs can probably be relativelylow since there are no field campaigns necessary to gather the data. Another striking factor which makesthe use of PS-InSAR favourable especially for the monitoring of dikes is that dikes contain a lot of PersistentScatterers. This is mostly due to the protective cover of the toe of most dikes which mainly consists of largebasaltic rocks. In between these rocks are open spaces which lead to very good reflections.

1

2 CHAPTER 1. INTRODUCTION

Figure 1.1: Potential coastline of the Netherlands without dikes [5]

1.1 Purpose statement

The purpose statement can be divided into three separate parts. The first part is the statement of work. Thispart describes the assignment of the project, with some boundary conditions. The project objective follows,this is the direct assignment from the project guide. The third part is the main research question, divided into4 sub-questions.

Statement of work: Explore the potential of detecting and monitoring deformation of water barriers in theNetherlands with satellite SAR Interferometric data carried out by 6 students during an 8 week period,leading to a report of the findings.

Project objective: “Perform an analysis, based on satellite synthetic aperture radar interferometric data, todetect and monitor deformation of water barriers in the Netherlands and give an interpretation of theresults. A combination of various sources of geo-information, as well as expert knowledge should leadto a well-balanced evaluation of the potential of the technique.” [39]

Main research question: Is the PS-InSAR technique feasible for dike (deformation) monitoring in the Nether-lands from a technical point of view?

This considers the feasibility of PS-InSAR for dike deformation monitoring based on the answers ofsubquestion 1, 2, and 3, considering the current needs for dike monitoring in the Netherlands, the diketypes in the Netherlands, and the needs of Dutch stakeholders in dike monitoring.

Sub questions:

1. What are the important characteristics of dikes with respect to PS-InSAR? What are the main physicaland geometrical characteristics of dikes which allow us to use PS-InSAR for dike monitoring. For example,the influence of the orientation of dikes, coverage layers of dikes.

2. Which types of deformation can be detected and which deformation mechanisms can be identified?Which deformation parameters can be derived from these observations considering different orbitalconfigurations and which deformation mechanisms can be identified?

3. What is the quality of the results of the PS-InSAR technique in dike monitoring? What is the precisionand reliability of the observations and the estimated deformation parameters. What is the quality of thediagnosis of the identified deformation mechanism?


1.2. RESEARCH METHODOLOGY 3

4. To what extent does PS-InSAR fulfill the needs for dike deformation monitoring in the Netherlands?This considers the feasibility of PS-InSAR for dike deformation monitoring based on the answers ofsubquestions 1, 2, and 3, considering the current needs for dike monitoring in the Netherlands, the diketypes in the Netherlands, and the needs of Dutch stakeholders in dike monitoring.

1.2 Research methodology

In this paragraph, the research methodology that is developed for the POSEIDON project is described. Theproject is divided into three different phases, because after each phase there are some documents that have tobe handed in. This is described in the Deliverable Items Description, see [38]. For each of those three phases,the research methodology is described individually.

Phase 1: Requirement analysis and project planning.

In this phase the requirements are specified, the stakeholders are identified and the project plan is made.Also the organization of the team is worked out. After this phase the baseline review has taken place.(See [34] for the product of this phase: the baseline report.)

Phase 2: Conceptual analysis, information gathering and combination and initial definition of case studies.

The conceptual analysis part of phase 2 describes our route towards a good level of knowledge on thesubject, which leads from literature study, through interviewing experts to performing forward modelsand studying inverse models.

The information gathering and combination can be divided into defining additional data sources, combinethem in one GIS package and getting experienced with the GIS package which will be needed in the 3rdphase.

The initial definition of case studies deals with the number of case studies, and it will also give a roughdetermination of interesting locations.

Phase 3: Detailed analysis of the defined case studies.

In the third phase a detailed analysis of the case studies will take place, using all information gatheredin the second phase. To combine all this information and data sets, the GIS environment is needed.In this phase the locations of the case studies as they are defined in phase 2 will be visited. Anothernecessity is to increase the number of interviews with various experts, preferably during fieldtrips, so thecase studies can be discussed one by one.

1.3 Boundary conditions

There are a few boundary conditions that can be defined. They limit the scope of the POSEIDON project andare listed below.

1. The feasibility of satellite SAR interferometry is researched, so no comparison with other methods isconducted.

2. This project focuses on the application of the Persistent Scatterer method for dike monitoring.

3. The POSEIDON project focuses on the monitoring of primary dikes in the Netherlands.


4 CHAPTER 1. INTRODUCTION

1.4 Structure of the report

After this introduction the report continues with chapter 2, which describes the existing water barriers, thedifferent dike deformation mechanisms and the current monitoring methods. After this, chapter 3 will explainthe Persistent Scatterer InSAR technique. After that, estimations of the dike deformation parameters aregiven in chapter 4. Detectable deformation mechanisms are presented, and the methods and results of ourforward and inverse modeling are explained. The report concludes with the methodology and overview of ourcase studies, which will be treated in chapter 5 and 6 and the conclusions and recommendations for furtherresearch in chapter 7.


Chapter 2

Dikes, deformation and monitoring

This chapter starts with a brief explanation of the basics of water barriers. A division of categories is made andthe structure of a typical dike is described. Hereafter we will explain the different deformation mechanisms andthe legal context of dike monitoring will be discussed. The chapter concludes with an explanation of differentdike inspection techniques.

2.1 Water barriers

In this section an overview of the different water barrier types in the Netherlands is presented. There willbe a distinction between categories and types of water barriers. The POSEIDON project will focus on non-natural water barriers, the reason for this is that artificial water barriers are expected to have better reflectioncharacteristics, see chapter 3.

2.1.1 Categories of water barriers

There are 17,000 kilometers of water barriers in the Netherlands. These can be separated into two categories,[20] , [22].

• Primary water barriers;

• Non-primary water barriers (e.g. secondary barriers, storage basin embankments).

In this chapter the further discussion is based on this classification.

Primary water barriers: The Netherlands has an extensive network of 3,700 kilometers of primary waterbarriers. These barriers offer protection against flooding by the North Sea, the Waddenzee, the largerivers (Rijn, Maas, IJssel), the Westerschelde, the Oosterschelde and the IJsselmeer. The primary waterbarriers mainly consist of dikes, only the North Sea coast is predominantly protected by dunes. Thenetwork of primary water barriers includes a large number of big dams and special constructions, likethe storm surge barriers in the Oosterschelde and the Nieuwe Waterweg. For a limited number of placeshigh grounds fulfill the function of primary water barrier. High grounds are areas that are sufficientlyhigh and broad to prevent water from flowing further, no management is necessary to maintain thissituation.

5

6 CHAPTER 2. DIKES, DEFORMATION AND MONITORING

Figure 2.1: Primary water barriers (in red) and dike-ring areas in the Netherlands [54]

The total length of the different kinds of primary water barriers in the Netherlands are [41]:

• 264 km dunes;

• 431 km sea dike;

• 1,433 km river dike;

• 535 km lake dike;

• 1,000 km of dike that is in front of other primary water barriers (e.g. the Afsluitdijk).

The Netherlands can be divided into separate areas which are each fully enclosed by water barriers.Such an area is called a dike-ring area (”dijkring gebied”). In total there are 57 dike-ring areas in theNetherlands (figure 2.1).

The primary water barriers have stringent safety standards. In the law on water barriers in the Netherlands(”Wet op de waterkering” [4]) the importance of these standards is assessed based on the nature of theflooding and the possible amount of damage in that area. For each dike-ring area there is a dedicatednorm, this is the average amount of times a year that the water level reaches the maximum that thedike must be able to withstand. For instance the norm 1/1,250 means that there is a chance of 1 to1,250 a year that the water level will reach the maximum of the dike. The most important areas in theNetherlands have a norm of 1/10,000.


2.1. WATER BARRIERS 7

The primary water barriers can be subdivided into five categories:

1. The water barrier belongs to a dike-ring area and blocks a body of water;

2. The water barrier belongs to a dike-ring area but does not directly block a body of water;

3. The water barrier lies in front of a dike-ring area and blocks a body of water;

4. The water barrier lies in front of a dike-ring area but is not intended for direct blocking of a bodyof water;

5. Primary water barriers outside of the Netherlands.

Water barriers belonging to category 1 are the last line of defense against inundation of salt water.Category 2 water barriers separate two dike-ring areas and they are the last line of defense againstfreshwater flooding. Behind the water barriers of category 3 and 4 there is no land, only water. Examplesof category 3 are the Afsluitdijk and the storm surge barrier in the Oosterschelde. An example of category4 is the northern part of the Grevelingendam, where there is water on both sides, this dam can be seenin figure 2.1 above the dike-ring area number 27. The function of water barriers of category 3 and 4 isto avoid or reduce the occurrence of high water levels behind them. This means they limit the load onthe category 1 and 2 water barriers. Category 5 water barriers exist where a dike-ring area passes theborder of the Netherlands, these are the dikes along the Rijn, Schelde and Eems. A dike failure in theseareas will possibly result in a flood in the Netherlands.

Non-primary water barriers: Non-primary water barriers consist of secondary water barriers, storage basinembankments and other types of embankment. Secondary water barriers protect the Netherlands againstfloods from other water systems. They lie within a dike-ring area and have the function of splitting upthat area. In this way they limit the area that would be inundated in case of a flooding, they can alsobe used as an escape route for people or transport of rescue-material.

Storage basin embankments (”boezemkaden”) lie within a dike-ring area and are there to protect apolder area from the water in the storage basin around the polder. Another function is to maintain thestorage basin, which has a buffer function in case of high waters. In contrast to secondary water barriers,storage basin embankments do have a direct water blocking function.

Other types of embankments were constructed to protect the dike-ring areas against water for the(smaller) rivers that run through the Netherlands. They have the function of blocking water comingfrom the rivers.

2.1.2 Types of water barriers

A major separation in types of water barriers can be made by distinguishing natural and artificial water barriers.Natural water barriers can be found along the largest part of the Dutch coast. The most important naturalwater barriers are the dunes, but also high grounds function as a natural water barrier. Dunes are a part ofthe natural landscape: they are formed by the wind and consist of sand in combination with vegetation. Thewater blocking function of dunes is solely due to the mass of the sand. This mass needs to be enough toprotect the land behind it even though there might be a lot of erosion.

There are 3 types of artificial water barriers for the protection of a dike-ring area against high waters. Theseare (figure 2.2):

Ground constructions: Dikes and dams are artificial earth bodies. In comparison to dunes dikes need to bemore erosion proof due to their smaller size. This is achieved by reinforcing the top layer with clay andgrass, a stone-like material or asphalt. Typical for this construction is the form, which is the same as atrapezoid. The water blocking ability of this construction is determined by the height and the strength.

Water blocking constructions: These constructions are made for another purpose that crosses the functionof water barrier. Such a function can be: shipping (sluices), a storm surge barrier, a water pumpingstation, a floodgate or a road passage.



Figure 2.2: The main types of water barriers [57]

Special water blocking constructions: Special water blocking constructions have the same function as theground constructions, but the form and materials used can be very different. Examples of special waterblocking constructions are embankments and walls. In this way a larger design freedom is achieved andmore functionality is possible. On the other hand more management and maintenance is needed. Thestrength of the construction results from the used construction materials like steel and concrete whichcan handle much higher stresses than clay. The global stability is achieved by friction with the ground,for instance with pilings.

The artificial water barriers of types 1 and 3 are made of a combination of clay, sand and basaltic rock. Thismaterial is available in large quantities, easily processed, flexible, very durable and simple to maintain. Insituations where water barriers cross (water) ways, artificial water barriers of type 2, like sluices and crossingsare made. These water blocking objects were formerly made of wood and brickwork, later also of concreteand steel. The amount of these constructions was generally limited because of the risk of not being able toclose them quickly enough.

Often there are other objects in the surroundings of water barriers, for instance buildings, roads, cables andtrees. These objects are there for other reasons than blocking water, but can influence the functioning of thewater barriers. Objects inside the water barrier ask for extra attention and extra maintenance. Pipelines formpotential leaks, buildings and trees can become a weak spot.

The difference between the types of water barriers and the related objects is not that evident. Specialconstructions can reinforce, complete or entirely replace ground constructions. Special constructions can befixed or be movable, while water blocking constructions are in fact nearly always movable special structures.

2.1.3 Structure of a dike

This section gives an overview of the general structure of dikes, the construction materials and how they arebuilt. Furthermore the general shape of a dike is described with some remarks on the dimensions.

Construction materials: Primary water barriers (as described in subsection 2.1.1) are usually made of clay,sand and boulder clay. Secondary dikes are usually made of a different material, like for instance peat.

A dike is built on a surface that has different subsoil layers each with their own characteristics. In somecases the subsoil is not strong/stable enough to build a dike on, in those cases ground improvement hasto be performed. This can be done by removing the top layer of the soil and replacing it with a moresuitable material. The rest of the dike is built on top of this.

The core component of primary dikes usually consists of sand, it is covered by one or two layers of(boulder) clay with a minimal thickness of 1 meter. This is because clay (in combination with grass)is best suited against erosion and does not let water through easily [32]. On the surface some extraprotection is added, on the inner slope and on top this is usually grass, and on the outer slope thisis a hard material like asphalt, basaltic rocks and rubble. These hard materials have good reflectivityproperties for radar; it does not absorb a lot of energy and signals can bounce back with more ease. Aschematic drawing of a dike can be seen in figure 2.3.


2.2. DESCRIPTION OF DEFORMATION MECHANISMS 9

Figure 2.3: Schematical drawing of a dike [50]

Shape of a dike: Dikes in the Netherlands can have different shapes, this is due to different demands on thedikes and a different historical background. Primary dikes have much shallower slopes than non-primarydikes. Dikes with a wider base are preferred because these are more stable and have more strength; onthe other hand they are also more expensive and take up more land. The top of a dike is about 2-4 mwide, but sometimes wider due to, for example, a road.

The maximal slope is determined by the soil type, each soil type has a natural slope at which the soiljust does not start sliding. For sand the proportion is 1 : 1 (that is at an angle of 45◦). Most dikeshave less steep slopes, for instance with a proportion of 1 : 4 (that is 14◦). These slopes can not be toosteep, because then the slope will become unstable, but it is also preferred that the slope must also notbe too shallow. This is an unnecessary use of material and space. The height of a dike is determinedusing regulations like the Delta-norm, these say that most primary dikes should have a height of atleast 10 meters above NAP. Every dike has a so called inspection report (”keur” in Dutch) in which theconstruction height of a specific dike is mentioned.

To prevent water flowing underneath the dike it is sometimes reinforced with an additional (smaller)body of material on the inner slope, this is because there is an increase of the dike length and water hasmore resistance flowing underneath the dike. Due to this extra material the dike now has the shape ofa long trapezoid with a smaller trapezoid on top. Something else that determines the shape of a dike isthe infrastructural need. Many dikes have roads or paths on top, these determine the minimal width ofthe top of the dike.

2.2 Description of deformation mechanisms

Several types of deformation of a dike can be distinguished. These types of deformation largely coincide withthe failure mechanisms of a dike. Failure mechanisms are commonly used in the field of dike monitoring to testthe dike for safety. They are mechanisms that may lead to breaching of the dike. In total there are 12 differentkinds of failure mechanisms that endanger the primary function of a dike, which is of course protecting the land



Figure 2.4: Overview of deformation mechanisms

from the water ([41],[17], [30] and [31]). These failure mechanisms are causes of deformation mechanisms,which are schematically explained in figure 2.4.

In this section the types of deformation are explained. Some of them are the same as the failure mechanisms,but when discussing deformation mechanisms we focus on the fact that there should be a visible deformationon the dike body. Most deformation types do cause the dike to fail. Table 2.1 gives an overview of alldeformation mechanisms, along with the failure mechanisms which cause the deformation, the magnitude anddirection of the effect, the duration of the process and the duration of the effect.

Erosion foreland: The foreland is the part of the outer slope below the water level. This part can collapsedue to sediment flowing over it. The sediment flow, which consists of matter like sand or clay mixedwith water, can take soil particles of the foreland with it, causing the foreland to loose its stabilityand therefore can collapse. Collapsing of the foreland can lead to collapsing of the whole outer slopeand after that the entire dike. Erosion of the foreland is a deformation mechanism as well as a failuremechanism.



Deformationmechanism

Failuremechanism(s)

Magnitude Directiondeformation

Durationprocess

Plastic /elasticdeformation

Erosion foreland Erosion foreland Different Horizontal +vertical

Endless Plastic

Erosion innerslope

Waveovertopping,overflowing

Different Horizontal +vertical

Up to 2 weeks(duration highwater)

Plastic

Erosion outerslope

Erosion outerslope

Different Horizontal +vertical

Up to 2 weeks(duration highwater)

Plastic

Horizontaldeformation

Deformationdue to highwater, nippingice, collision

≤15 cm Horizontal Up to 2 weeks(duration highwater), collisionis seconds

Elastic / Plastic

Piping Piping small craters Forms craters Endless, up to acouple of daysper crater

Plastic

Seepage Seepage <5 cm uplift vertical Mainly duringhigh water

Elastic

Settlement Settlement Up to 50 cm,stretching up to10 m form toe

Vertical Exponentialdecreasing

Plastic

Sliding Sliding Announces itselfwith ≤15 cmelasticmovement

Horizontal Up to a minute Plastic,announcementis elastic

Sliding innerslope

Sliding innerslope, microinstability

Announces itselfwith mmreplacement,later meters

Horizontal +Vertical

Seconds,announcementyears

Plastic,announcementis elastic

Sliding outerslope

Sliding outerslope

Announces itselfwith mmreplacement,later meters

Horizontal +vertical

Seconds,announcementyears

Plastic,announcementis elastic

Slidingprotective cover

(erosionforeland)

decimeters Horizontal +vertical

Seconds,announcementdays

Plastic,announcementelastic

Subsidence Subsidence Depending onsource ofsubsidence, upto meter

Vertical As long as thecause ofsubsidencecontinues (togrow)

Plastic

Swelling Micro instability Few mm Horizontal +vertical

Up to a fewmonths

Elastic

Table 2.1: Deformation mechanisms



The magnitude of this deformation depends on the rate of flow of the sediment flows in the water bodynext to the dike. The deformation is plastic and remains until this flow vanishes. The direction of thedeformation is in both the horizontal plus the vertical plane.

Erosion of the inner slope: Erosion of the inner slope can be caused by 2 different failure mechanisms, thefirst is wave overtopping, the second is overflowing. If the process of erosion continues long enough, itcould cause a breach in the dike. The deformation mechanism is therefore very dangerous for the dike.

Overflowing takes place if the water level in front of the dike exceeds the height of the dike. An exampleof overflowing can be seen in figure F.1. This can occur when the water level is higher than the dike isdesigned to handle. It can also be that the dike has become lower during the years so that it is not ableto handle the water level that it was designed for anymore. There are a lot of deformation mechanismsthat cause a dike to loose height, like settlement, erosion or sliding of the slopes. Possible causes forthe higher water level can be a rise in the sea level, heavy precipitation, wrong calculations or just notenough data at the design phase to predict the water level correctly.

Wave overtopping occurs when there is a combination of a high water level and large wave amplitude.These waves can be caused by passing ships or a storm. To make a distinction between wave overtoppingand overflowing, the dike should be higher than the actual water level, but should not be high enoughfor stopping the waves. Wave overtopping leads to erosion of the top and inner slope of the dike, whichcan cause the dike to breach because of sliding of the inner slope. An example of wave overtopping canbe seen in figure F.2.

The magnitude of this deformation depends on the rate of flow of the water over the dike. Thedeformation is plastic and keeps on going until this flow vanishes. The flow vanishes if the water leveldecreases, which is usually after about 2 weeks. The direction of the deformation is in both the horizontaland the vertical plane.

Erosion of the outer slope: At first sight, erosion of the outer slope is very similar to sliding of the outerslope. The difference is that erosion is a slow process, where soil particles which the dike consists of areswept away by currents and waves. Sliding of the outer slope will cause a much faster deformation ofthe dike, since the whole slope will slide down at once. Another difference with sliding of a slope is thaterosion of the outer slope only occurs below the water level. Erosion can cause sliding of the slope, ifenough particles are taken away. The danger of erosion is that it cannot be seen until the water retreats.

The magnitude of this deformation depends on the rate of flow of the sediment flows in the water bodynext to the dike. The deformation is plastic and keeps on going until this flow vanishes. The directionof the deformation is in both the horizontal and the vertical plane.

Horizontal deformation: There are a number of failure mechanisms that cause horizontal deformation. Thefirst is collision, although that mainly causes damage to the protective cover of the outer slope. Thesame holds for the second failure mechanisms that causes this type of deformation, which is nippingice. A third failure mechanism is deformation due to high water. All failure mechanisms that causehorizontal deformation will be treated here.

The mechanism collision is simply a ship colliding with the dike, causing damage to it. A dike shouldalways be strong enough to resist a collision like that. The upper layer of the dike will probably bedamaged. This leads to faster saturation of the dike, because the soil beneath the protective layer isnow unprotected. Saturation is a danger because it leads to micro instability, a failure mechanism thatwill be explained later in this chapter. A collision can also cause the dike to be pushed landwards, justbecause of the pressing force of the ice. If the protective layer is not strong enough to withstand theincoming ship, the dike could also breach.

Nipping ice is the phenomenon of small ice plates, piling up along the dikes, therefore putting pressureon the dike. Just like collision, the protective cover is endangered first. Due to the pressure of the ice,the dike might also be pushed landwards. This effect is the horizontal deformation that is discussed inthis section (see [18]). At locations where ice nips, erosion can occur. The damage must be repaired assoon as the ice has melted. There is a chance that after the winter period other failure mechanisms willoccur, because the protection layer is damaged.

High water is a temporal effect with a maximum period of 2 weeks. The pressure of the water againstthe dike results in a horizontal deformation of the dike. The deformation is the biggest at the upper



part of the dike. After the water level has decreased to its normal level, the dike will (almost) returninto its original state. The horizontal deformation can be up to 15 cm.

The deformation is mostly in horizontal direction, and keeps going on until the cause vanishes, which isusually after 2 weeks (in case of nipping ice and high water) or after a few seconds (in case of collision).

Piping: It is commonly known that high water levels cause water to seep underneath the dikes. This is becausethe high water pressure forces the water to travel to the lower lying areas. In most cases, the water willtravel through weak spots in the lower ground layers, and form pipes. This seeping water will becomea danger to the stability of the dike if it transports materials from the dike, such as sand. This willhappen if the ratio of the height difference to the length of the pipe is greater than 7% (Mr. Vrijling,Delft University of Technology, oral communication, 28 September 2006). If enough sand is removedfrom under the dike, the dike will become unstable. Piping frequently results in wells, see figure F.4.

The deformation process leaves small craters in the landscape just behind the dike. These craters canmeasure up to a few meters in diameter. The process lasts for a few days per crater, but over all a dikebody is continuously threatened by this phenomenon. The deformation is plastic.

Seepage: If the water level on one side of a dike is higher than the land on the other side, some water sill seepthrough the dike and soil layers under the dike towards the land. This effect increases if the differencebetween the water level and the height of the land increases. The seeping water makes contact withthe ground water on the land side of the dike, which causes an upwards pressure under the land. Thisupwards pressure translates into an upwards motion of the land, which can be measured as deformation.

The uplift depends heavily on the soil characteristics and can be up to about 5 centimeters in case ofextremely high water and a thin upper layer of soil (Mr. van Baars, Delft University of Technology, oralcommunication, 6 October 2006). The deformation will start as an elastic deformation, and can getplastic if the water pressure is too high for the upper layer of soil next to the dike. The deformationoccurs in the vertical plane.

Settlement: Settlement is a deformation mechanism that mainly causes deformation in the vertical directioni.e. the dike becomes lower. The danger of settlement is that the dike loses too much height to preventfailure mechanisms like wave overtopping and overflowing. The settlement rate is dependent on thelocation, way of construction and construction material which is used to build the dike.

The deformation happens mainly in the vertical plane. The most important effect is the settling ofthe soil layers directly under the dike, which occurs due to the weight of the dike. The settlement istherefore a very local effect around the dike, and stretches up to 10 meters from the toe of the dike.The effect lasts throughout the whole lifetime of the dike. The magnitude of the effect can be up to 50centimeters, with a speed of a few centimeters a year. The speed decreases with time. The magnitudedepends on the composition and weight of the dike, and on the composition of the soil beneath the dike.The deformation is largely plastic, if the dike is removed the soil might show some uplift, but will neverreturn to the original state.

Sliding: Sliding of the whole dike is somewhat similar to sliding of the inner slope. The process starts witha horizontal elastic landwards deformation because of the water pressure. This may become a plastichorizontal movement when the water pressure exceeds the strength of the dike, causing the entire diketo slide horizontally. The strength of the dike is dependent on the weight of the dike, the density ofthe used construction materials and the capability of the construction material to dissolve in water. Anexample of a plastic horizontal sliding of a dike is given in figure F.5.

The effect itself is, as can be seen in figure F.5, plastic and quite large. The effect is very rapid aswell; the sliding is completed within a few seconds. The effect that announces the sliding is smaller andhappens at a smaller speed. It is a mainly elastic deformation, and can be compared with a combinationof settlement due to dryness of the dike, and horizontal deformation due to high water. The dike startsto tilt a bit landwards due to the pressure of the water, while getting smaller because of the lack ofwater in the dike body. Sliding is only likely to occur in case of dry peat dikes.

Sliding of the inner slope: The inner slope is the land side slope of the dike. This slope can becomeunstable due to various reasons. When large amounts of water are passing the dike, for example becauseof overflowing or wave overtopping, the water can soak the inside of the dike. This will lead to ahigher internal water pressure of the dike and less friction resistance because of the saturation of the



soil particles. The state of the dike at that moment is referred to as micro-instability. Micro instabilitycan cause sliding of the inner slope. Cracks in the inner slope will speed up the sliding process.

Sliding of the inner slope does not necessarily have failure of the dike as a consequence. It will definitelyweaken the dike, but as long as the top of the dike stays at the same height, the area behind it will notflood immediately but some reparations are really necessary (as can be seen in figure F.6). If the toplowers as well, the height of the dike decreases which can cause immediate overflowing and eventualbreaching of the dike.

The effect is a horizontal and vertical plastic deformation. It announces itself by a small deformation, inthe same direction as the plastic deformation. The announcement is mainly elastic. It is a combinationbetween swelling and some incipient ruptures and minor slides. The announcing effect can last severalyears and is on millimeter level.

Sliding of the outer slope: Sliding of the outer slope often occurs after a period of high water, followed bya fast decrease of the water level, but it can also occur during a high water period. The first scenariois caused by the following sequence of events: When the water level is high, the dike will get saturatedwith water. If the water level then drops, the water which is trapped in the dike cannot flow down. Dueto higher pressure of the top part of the dike the outer slope will slide down.

Sliding of the outer slope during a period of high water is caused by erosion of the foreland/ outer slope.This leads to a removal of the base of the dike, which leads to a slide. Just like other sliding effects, theannouncing effect is of millimeter magnitude. The effect consists of erosion of the foreland or the outerslope, and is therefore plastic. A minor deformation of the dike body can as well be seen; one shouldthink of some tilting towards the area where the erosion takes place.

Sliding of the protective cover: Sliding of the protective cover is similar to sliding of the outer slope, withthe difference that only the upper layer slides down. This deformation mechanism causes a change ofthe surface of the dike. The main cause of this is erosion, which can cause the stones which cover mostdikes to become unstable and roll down. It could also be inflicted by the loss of roll resistance in thelayers beneath the protective cover.

Subsidence: Subsidence is a vertical deformation of a large area, including the dike. This can be caused bygas extraction or salt mining for example. The consequence is that the dike and its surrounding areawill deform in vertical direction. When this happens (whereas the water level will not decrease) the dikecan become lower than its required height, which gives a higher risk of overflowing.

Swelling: Swelling is a temporal effect, where the dike will get saturated with water for example due toextraordinary rainfall or high water. This will cause a slight increase in size of the dike.The magnitudeof the effect is dependent on the construction material of the dike. A sandy dike is not likely to getsaturated with water, because the sand particles are not able to hold the water, whereas dikes which aremade of clay or peat are likely to get saturated with water.

Swelling can, along side of micro instability, be the result of saturation. A reaction of the dike to swellingcan be the sliding of the inner slope caused by water pressures inside the dike. The second is the flushingaway of soil particles due to the leakage of water.

Swelling is a small effect which has always been hard to measure. It is an elastic deformation, and iscaused by saturation of the dike body with water. The period of the deformation is a few months atmost.

2.3 Legal context of dike monitoring

The first part of this section deals with the responsibility for the dikes in the Netherlands. The second partgives some insight into what legal issues will be relevant if some weaknesses in the dike system are found.


2.4. CONVENTIONAL GUIDELINES FOR DIKE MONITORING 15

2.3.1 Responsibility of dike monitoring

The waterboards make a division between primary dikes and non-primary dikes. Primary dikes are majorbarriers that protect the land from open water, like sea, lakes and rivers. Non-primary dikes are barriers thatprotect land from small water flows, like canals and creeks. The non-primary dikes have mainly the functionof preventing (rain) water problems.

According to [8] the primary dikes are, in 90% of the cases, the responsibility of the waterboards. The other10% is maintained by the state. Examples of primary dikes maintained by the state are the Afsluitdijk, theOosterscheldekering and the Maeslantkering. All non-primary dikes are maintained by the waterboards.

The Provincial Parliament has the task of controlling and checking the work of the waterboards within theirown province. The final end responsibility is with the secretary of state of the Ministry of Transport, PublicWorks and Water Management.

2.3.2 Legal issues using InSAR for dike monitoring

The law on the water barriers of the Netherlands does not state a definite way in which the dikes should bemonitored (see [26] for the whole law text). It does say that the ”Voorschrift Toetsen op Veiligheid” (see [54])should be followed. This document literally sets down the format and the inclusions which a dike-stabilityreport should have (see section 2.4 for a detailed description of those inclusions). This document states thatthe height of the dike could be monitored with leveling, but other methods are also allowed, if specified in thedike-stability report. Other examples mentioned are tachymetry and helicopter laser altimetry. The result ofthe ”Voorschrift Toetsen op Veiligheid” is that any measurement method will be sufficient, as long as it isscientifically proven to work, and its accuracy known and described as well.

If unsafe areas are found, therefore causing properties of people living behind the dike to devaluate, there willbe consequences for the waterboards, because they are responsible for the good condition of the dike. If newunsafe areas are found, the waterboards are to blame for that.

2.4 Conventional guidelines for dike monitoring

The assessment of the safety of dikes is based on a subdivision of the main parameters of a dike. The waythe dikes will be able to protect the area behind them against inundation, will depend on the height of thedike and/or its stability. Signs of deformation can be observed during the stability inspection and comparingthe crest height margins of two height inspections. Therefore, these main parameters will be discussed nextin separate sections.

2.4.1 Height inspection

The failure mechanisms that are dependent on the height of the dike are overflowing, wave overtopping andsettlement. Whether the dike is able to fulfill its safety function for the area behind it depends on twoparameters, namely the crest height margin and the amount of tolerable water discharge. The crest heightmargin (”kruinhoogtemarge” ) is the difference between the crest height of the dike and the water level inleading circumstances, which includes the expected water level rise until the reference date and some additionsfor the expected weather oscillations. The amount of tolerable water discharge (”overslagdebiet” ) is themaximum amount of water that may come over the dike, which the pumping stations still can handle. Thejudgment of the crest height can be defined in three steps, which have an increasingly detailed procedure.When the result of the first and most simple method is sufficient, its not necessary to perform the othermethods. These steps are given in figure 2.5 schematically.



Figure 2.5: Schematical overview of height testing procedure.

Step 1: Simple testing The simple testing method of step 1 is based on the design conditions (e.g. thewater level) the dike is designed to handle. This way of testing is only possible when the used designconditions have proved to be favorable with respect to the current testing conditions. This means that:

• The expected water level rise until the reference date plus the additions, wave amplitude and waveperiod should be the same or less than the designed ones

• The crest height including the settlement cannot be lower than the designed height of the dike

• The slope of the dike may not be steeper than the designed value

• The amount of tolerable water discharge cannot be smaller than the designed value

To be able to test those conditions, it is necessary that the actual crest height is known and that thesettlement of the dike is estimated. When these conditions cannot be fulfilled, the testing must proceedto the next step. An advantage of the first step is that no calculations are needed. It is only necessaryto compare the current parameters with the design parameters.

Step 2: Detailed testing The second, detailed testing method is applying the calculations from the guide-lines for dams, sea- and lake dikes [58] or the guidelines for river dikes (see [55] and [56]), dependenton the dike type. The first thing that should be calculated (see [59]) is the amount of tolerable waterdischarge, belonging to the crest height and the slope of the dike.

• If the amount of tolerable water discharge is smaller or equal to 0.1 l/m/s it is considered negligibleand then the crest height margin is calculated. When the crest height margin is more than 0.3meter it is ”sufficient” (if it is 0.5 meter or more its excellent), but when it is less than 0.3 meter,advanced testing is necessary (step 3).

• If the amount of tolerable water discharge is bigger than 0.1 l/m/s but smaller than 10 l/m/s, theinfluence on the inner slope should be tested. This influence is strongly dependent on the typeof protective cover on the inner side of the dike. When this cover consists of stone or asphalt,it is assessed as ”excellent” as long as the crest height is bigger than the water level in leadingcircumstances and the amount of tolerable water discharge is coming from 2% or less of thetotal number of incoming waves. When this cover is grass, it has to be tested for erosion andsliding of the inner slope, for other types of protective cover the specialists have to step in. Whenthe protective cover gets a judgment ”insufficient” this is also the final assessment, when it is


2.4. CONVENTIONAL GUIDELINES FOR DIKE MONITORING 17

”sufficient” or ”excellent” the crest height margin has to be checked. Then the same holds as inthe previous situation, that when the crest height margin is more than 0.3 meter the assessment is”sufficient” (if its 0.5 meter or more its ”excellent”, but this is only possible if the protective coverwas excellent as well), but when its less than 0.3 meter, advanced testing is necessary (step 3).

• If the amount of tolerable water discharge is 10 l/m/s or more, the crest height margin plays acrucial role in the further testing method. When this margin is less than 0.5 meter, the assessment”sufficient” can only be given after advanced testing (step 3). When the margin is 0.5 meter ormore, this is large enough to exclude overflowing and only consider wave overtopping. With atolerable water discharge of 10 l/m/s or more, the crest of the dike is not passable for inspectionor reparation work and it has to be proved that this does not endanger safety. If it does, the finalassessment is ”insufficient”. When it is not necessary that the crest of the dike is accessible, thefinal assessment is dependent on the measure of storage and discharge possibilities. If they arerestricted in such a way that the wave overtopping will endanger the safety, the final assessment is”insufficient”. If it causes an unacceptable amount of superfluous water but it does not endangersafety, the final assessment will be ”sufficient”. If it causes no (unacceptable) amount of superfluouswater it will get the final assessment ”excellent”.

Step 3: Advanced testing The third and final step is the advanced testing, which has to be performed byspecialists (the first and second step can be conducted by the bodies responsible for dike monitoring).They have to set up a testing method which is specifically designed for the dike that is being tested.They will check whether the uncertainties in the water level in leading circumstances are covered by thecrest height margin and whether its safety will be preserved.

2.4.2 Stability inspection

Just like the height inspection which was described in the previous section, the stability inspection can alsobe divided into three different degrees of detail. The stability of a dike is dependent on more parameters thanjust the height of a dike, so much more failure mechanisms have to be tested. It also includes parametersthat are more difficult to observe than the current height and water level in leading circumstances of theprevious section. Therefore the stability testing is split into four main types of failure mechanisms, namelypiping, micro instability, sliding of the outer slope and sliding of the inner slope. For each of those four typesof mechanisms, the three testing methods (simple, detailed and advanced) are applied.

Step 1: Simple testing The way the first step, the simple testing method, will be applied is dependent onthe used construction material and the soil types at the location of the dike. There are 4 different typesthat can be distinguished, namely primary dikes made of clay, primary dikes made of sand which arebuilt on either a good or a bad water passing soil type. For each of those dike types, a geometrical testand testing of the used design method are performed, where only simple calculations have to be usedwhich can be found in [54].

Because most of the dikes in the Netherlands were built before the design guidelines came into existence,it is necessary that their designs are checked for safety. For instance, sufficient soil research must becarried out. Furthermore, it has to be checked that, at the time of the design of the dike, the designershad sufficient knowledge of the stresses and the potential of the water under leading circumstances.Lastly, the accessibility of the dike when the safety is in danger should be accounted for.

Step 2: Detailed testing The second, detailed testing method is based on data collection or based on ap-plying the calculation models of the guidelines (see [55], [56] and [58]). This data collection can onlyconsist of enumerating the existing data or performing some additional soil research. Examples of addi-tional soil research are measuring the water tensions inside the dike or in the subsurface or researchingthe layering of the subsurface of the area behind the dike.

Step 3: Advanced testing The advanced testing method is based on the state of the art knowledge of thespecialists on the failure mechanism, advanced calculation models, etc. But before these advanced testswill be performed, there will be some research done by specialists on the feasibility of the advancedtesting and the necessity of those models.



Figure 2.6: Crumbling of basaltic stones [42].

2.5 Dike monitoring in practice

The parties that are responsible for maintenance and inspection of the primary dikes, have to test and reportthe status of their primary dikes every five years to the Provincial Parliament in accordance with the guidelinesas described in the previous section (see [49] or [47] for an example of such a report). But this is not the onlytesting, which is done by the responsible parties (for most of the primary dikes, these are the waterboards).They also conduct a so called dike watch (”dijkschouw” in Dutch) with a written report once or twice a year.Unreported dike watches are, in some cases, conducted daily. After storms and other dangerous events, a dikewatch will be conducted. In this section, the method how the reported dike watch is conducted is explainedbriefly.

The most important goal of the dike watch is the prevention of unsafe situations. It also gives the waterboardsa good opportunity to get insight into the state of maintenance and they can keep their data of the dikes upto date. The dike watch is a broad visual inspection where the maintenance state of the dike and possibledamage are checked. The dike watch splits the primary dikes into four different areas of interest, namely theouter slope, the dike crest, the inner slope and the vegetation on the dike.

The first part of the primary dikes that is watched carefully is the outer slope. The outer slope of the primarydikes is mostly protected with a layer of (basaltic) stones. The quality of those stones is decreasing with time.This is because after years of exposure to sunlight, salt, water and wind, the basaltic stones will crumble. Thiscan be seen in figure 2.6, where the smooth basaltic stones are lying next to the crumbled ones. The dikemaintains its strength, because those crumbled stones are captured between the smooth stones, but they haveto be replaced in time.

The crest of the dike is mostly checked on its height, but also some cracks on this part of the dike are monitoredcarefully. They can be used to indicate whether a slope of the dike is going to slide downwards. The innerslope is mostly checked for seeping water and resulting wells. These are signs that something has changedwith respect to the stability of the dike.

Testing the vegetation on the dike is a legal obligation, which has to be performed every 5 years, [26]. Dueto practical reasons, most of the waterboards choose for a division of their primary dikes, so each year onepart can be tested carefully. The testing aspects are for example the amount of different species and the rootpenetration. The presence of weed between the stone cover at the slopes also gives a drawback: It makes thequality assessment of the stone covers difficult or even impossible.


2.5. DIKE MONITORING IN PRACTICE 19

Figure 2.7: The FliMap system [14]

2.5.1 Used measurement techniques for dike monitoring

There are several acquisition techniques in use to obtain information of the dikes. The most common methodsat this moment are leveling, GPS-RTK, FliMap r© and Ground Penetrating Radar. These methods will beexplained in this section. There are also some other measurements techniques where the application of dikemonitoring is still in a research stage. For further information, see for example [51] and [11].

Leveling This is the oldest way to obtain height information and deliver data with millimeter precision. Thistechnique is still used, because newer techniques can not meet this order of accuracy. The methodis especially used during and after dike reinforcement to monitor the crest height and settlement bymeasuring the crest height. When these data are stored, future height measurements can be comparedwith the old measurements to assess the deformation in between.

GPS-RTK The GPS-RTK (Real Time Kinematic) technique delivers data with an accuracy of a few cen-timeters. This method is used in cases where less precise height information is required, for examplefor measuring profiles, quantity survey and to obtain topographic information. But it is also an usedtechnique to measure horizontal deformation.

FliMap r© FliMap r© (Fast Laser Imaging - Mapping and Profiling) is a system from the company Fugrothat uses LiDAR (Light Detection And Ranging) in combination with high-resolution photo and videoimagery, to monitor railroads, dikes etc. As platform a helicopter is used. The position of this helicopteris known by the use of GPS-RTK (see figure 2.7). The advantage of a helicopter above an airplane isthat a helicopter can fly slower and at a lower height. This means that the point clouds obtained bythe laser system are of a higher density, and that means also a higher accuracy, which can be up todecimeter level. Out of this data, a lot of information can be extracted such as height models, profilesand positions of water embankments.

Ground-penetrating radar A ground-penetrating radar (GPR) system uses two antennas, which are mostlya fixed distance apart. One is a transmitting antenna, which emits an electromagnetic wave field intothe ground, and the other is a receiving antenna, that records this field and its reflections from thesubsurface. When an electromagnetic wave propagates through the ground and detects a soil layerwhere the electric and/or magnetic properties of the ground change, part of its energy will be reflectedback to the receiving antenna and part of it will be transmitted through the soil layer. It is mostly usedfor the detection of soil layers and objects beneath the surface, but also the groundwater level can bedetected easily, because it is a strong reflector (after [40]).


Chapter 3

Principles of deformation monitoringwith radar interferometry

In this chapter, the principles of radar interferometry for deformation monitoring will be explained. The firstpart contains the basic idea of interferometry, which can be used to measure topography and deformationparameters. After that, it will continue with an explanation of the conventional Interferometric SyntheticAperture Radar (InSAR) method and its main characteristics and limitations. Finally, the more advancedtechnique ”Persistent Scatter InSAR” (PS-InSAR) will be introduced and the main advantages and limitationsof PS-InSAR will be discussed.

3.1 Introduction to InSAR

Since the early 1960’s, radar imagery has played an important role in remote sensing science and has opened aworld of new applications in geosciences. Early experiments of synthetic aperture radar (SAR) sensors showedthe good performance of the SAR systems in mapping the earth surface and acquisition of physical propertiesof the earth. In contrast to optical remote sensing sensors, which are passive sensors and measure the sun’sradiation reflected from the ground, radar sensors do not need solar illumination. Radar satellites activelyilluminate the earth and record the amplitude and phase of the backscattered waves. Furthermore, becauseradar waves are in the microwave regime of the spectrum (with a typical (long) wavelength of about 5-25cm) they can travel through clouds. This means that radar satellites can operate day and night and almostindependently of meteorological conditions.

Compared with optical sensors, one limitation of a radar or SAR system is in the incapability of measuringangles. ”Similar to a single human eye, which is essentially blind for the difference in distance to the object,it is impossible for a radar or SAR to distinguish two objects at the same range (but different angles) to theinstrument. Nature readily provides the simple solution for the problem: the use of two sensors. It workedwith two eyes, why not use two radars?” ([37]). This is the basic idea behind the interferometry.

Using the principle of interferometry and by using the phase measurements of two SAR images, it is possibleto measure the variations in the distance between the satellite and the earth’s surface due to topography anddeformation. Today, InSAR is generally known as a powerful tool for detection of surface displacements overlarge temporal scales with precision in the cm and even mm range. This possibility causes InSAR to find usefulapplications in different fields such as earthquake and volcanic studies, glacier monitoring and land subsidencemonitoring due to the mining, gas, water, and oil extraction.

The purpose of this chapter is to review the principles of conventional SAR interferometry and to describe amore advanced InSAR technique (PS-InSAR) for deformation monitoring and the main issues concerning the

21

22 CHAPTER 3. DEFORMATION MONITORING WITH RADAR INTERFEROMETRY

Figure 3.1: Phase measurement, [19]

interpretation of its results.

3.2 Conventional InSAR

In this section, the main characteristics of conventional InSAR are discussed. First the interferometric pa-rameters are described, followed by the limitations of conventional InSAR. Despite the valuable application ofInSAR in mapping the topography, the focus is here on the application of InSAR in deformation monitoring.

3.2.1 Basic idea

Deformation monitoring using InSAR is based on the principle of distance measurements with electromagneticwaves. If the sensor transmits a pulse to the object and records the return pulse, the time difference betweenthese two pulses shows the distance between the sensor and the object. In other words, the time delay of theecho (reflected pulse) measures the distance of the sensor to the object. This time delay can be measured asthe phase difference between transmitted and received wave. With two acquisitions, the difference in measuredphases shows the variation in the sensor-object distance.

Similarly, a SAR sensor transmits a signal to the earth and measures the amplitude and phase of the backscat-tered signal. The phase of the signal that is backscattered from the radar target on the earth, is related tothe sensor-target distance. A SAR image is actually a set of pixels characterized by both amplitude and phasevalues. In interferometry the amplitude of the received wave is ignored. Instead, the phase of the wave isused. Assume that two different radar images are obtained from exactly the same position in space. If nothinghas changed, the measured phase of the second image should be exactly the same as the previous phasemeasurement in the first image. If there is any change in distance between the satellite and the earth’s surfacedue to deformation, the phases will differ (see figure 3.1). This phase difference shows the deformation in thedirection of the satellite’s Line of Sight (LOS). By creating an image of these phase changes, it is possibleto map deformation with the precision of a small fraction of the radar wavelength. This image is called aninterferogram. The phase changes occur in the interferogram as fringes (see figure 3.2).


3.2. CONVENTIONAL INSAR 23

Figure 3.2: Interferogram of Bam : The interferogram of Bam (Iran) constructed from two radar images, onebefore and one after an earthquake has taken place. Each of the colored interference fringes is equivalent to a28 mm contour (half the wavelength) of surface deformation in the satellite’s LOS. The phase measurementsare relative, so to calculate the deformation at each point one should count the fringes from the edge of theinterferogram to that point and multiply it by 28 mm.

The above discussion is based on the assumption that both images have exactly the same acquisition geom-etry and that the only change between two images is the deformation of the surface. However, in practicethere are other factors causing differences between two images, such as atmospheric conditions, acquisitiongeometry and scattering characteristics of the targets. These factors superimpose some phase differences onthe interferometric phase measurements. These effects will be described in the next section, as well as otherparameters that affect the interferometric phase observations.

3.2.2 Main interferometric parameters

As mentioned before, the InSAR technique for deformation monitoring is based on phase shift measurements.However, not only a deformation of the surface causes a phase change, also other factors introduce additionalphase shifts. So, the interferometric phase observation per resolution cell (pixel) contains the contribution ofdifferent factors [37]:

φ = 2πk + φtopo + φdefo + φatmo + φscat + φnoise

= 2πk +4πB⊥

λR sin θH +

4π

λD + φatmo + φscat + φnoise. (3.1)

Where:



φatmo Phase shift due to the atmospheric delayφdefo Phase shift due to deformationφnoise Noise (e.g. thermal noise, coregistration errors, and interpolation errors)φscat Phase shift due to a change in the scatter characteristics of the earth surfaceφtopo Topographic phaseλ Radar wavelengthθ Incidence angleB⊥ Perpendicular baseline (distance between the satellites)D Deformation in the radar LOSH Height above the reference framek Phase ambiguity, the unknown integer number of full phase cycles.R Slant range from the master platform to the earth surface

As can be seen in equation 3.1, there are different parameters that affect the interferometric phase observation.Because the feasibility of the InSAR technique for this particular application depends on these parameters, weshortly describe each parameter in this section.

The interferometric parameters can be divided into two main groups [36]: design parameters and environmentalparameters. The main design parameters are the radar wavelength, the perpendicular baseline, the time intervalbetween the image acquisitions (temporal baseline), the incidence angle and inclination, and the total numberof available images. The second group, the environmental parameters, consists of the earth’s atmosphere, theearth’s surface, and the specific deformation characteristics.

Design parameters

Radar wavelength: As deformation in the LOS is measured as a fraction of the wavelength, the precision andaccuracy of the estimated deformation depend directly on the radar wavelength. This implies that theshorter the used wavelength, the more accurate the deformation vector that can be obtained. However,as short wavelengths are scattered by small objects, random movements of these small objects disturbthe phase signal analysis. So in this case a larger wavelength is often preferred. On the other hand, avery large wavelength (larger than 24 cm) will suffer more from disturbances caused by the ionosphereand other radio interference.

Perpendicular baseline: The perpendicular baseline has two major influences on the phase observation. First,the perpendicular baseline determines the sensitivity to a difference in topographic height. As can beseen in equation 3.1, the topographic phase is proportional to the perpendicular baseline. This impliesthat, if the perpendicular baseline is zero, the topographic phase will be zero as well. This situation isideal for deformation measurements as the superposition of topographic phase is removed. However,the assumption that two images are taken from exactly the same location is unlikely in practice andphase observations usually contain a topographic phase. Using external elevation models or high qualityInSAR acquisition without deformation signal (Differential InSAR), topographic phase can be removed.Because of an inaccuracy in the elevation models, some residuals from the topographic phase are left.In this case, after removing topography, equation 3.1 becomes [37]:

φ∆H = 2πk +4πB⊥

λR sin θ∆H +

4π

λD + φatmo + φscat + φnoise, (3.2)

Where:φ∆H the differential phase∆H the topographic phase residual

The second effect of a perpendicular baseline on the phase observation is due to looking at the earthfrom a different imaging geometry. This difference causes the radar reflection at the earth’s surface tobe changed and introduces a new effect as the phase noise. So, the phase noise is proportional to theperpendicular baseline. In radar interferometry, this effect is called geometrical decorrelation.

Temporal baseline: Another design parameter is the temporal baseline. This parameter is a multiple of thesatellite’s revisit interval, which is for example 35 days for the ERS-1, ERS-2, and Envisat missions.The temporal baseline should be large enough to detect the deformation mechanism of interest. On


3.2. CONVENTIONAL INSAR 25

the other hand, a large temporal baseline causes the phase observation to become noisier due to thetemporal decorrelation. This effect is because of the changes in scattering characteristics of the targetsin large time interval and makes it difficult to find corresponding pixels in two images.

Incidence angle, inclination and number of images: Other design parameters are the incidence angle, theinclination and the number of available images. Using different combinations of interferograms, the effectof the incidence angle and the inclination can be altered. The fact that most of the radar satellites are ina near-polar orbit leads to difficulties in deriving the north-south component from the LOS deformation.This leads to worse accuracies in the north-south component. A satellite with an inclination of about60 or 120 degrees would enable the processors to solve all three components properly [60]. The totalnumber of acquisitions is important because many different images enable the processors to recognizehigh-quality pixels and to optimize the ratio between the deformation signal and atmospheric error signal[36].

Environmental parameters

Atmosphere: The atmosphere delays the radio waves and introduces an additional phase shift in the observa-tion (φatmo). The amount of atmospheric disturbance depends on the climate conditions and the localweather situation. The magnitude of these delays can be up to several centimeters. Since a potentialdeformation is measured relatively between points in the image, a larger distance between points resultsin an increase in the atmospheric error signal [36].

Deformation characteristics: Deformation characteristics are other important parameters which can definethe potential the InSAR technique for particular application. Deformation mechanisms are very difficult torecognize if they have a similar impact on the measurements as the satellite orbit error or the atmosphericphase shift. Furthermore, the velocity of the deformation plays an important role. For instance, asudden deformation due to an earthquake or a landslide is easier to detect than slow deformation due tosubsidence or tectonic movements. Another issue is that the deformation gradients between neighboringpixels should be smaller than the radar wavelength in order to be detectable.

Land surface: The most important environmental factor is the reflective surface of the earth. SAR interfer-ometry only works under coherent conditions, where the received reflections are correlated between thetwo SAR images [37]. Therefore, any change in reflection characteristics in the pixel area causes the lossof coherence or (temporal) decorrelation. For example, a water area is useless for interferometry due tothe fast changes in the water’s physical characteristics. Usually, urban areas have a better coherence intime than agricultural and heavily vegetated lands. As an illustration, the city of Bam and the town ofBaravat have a very low degree of correlation (see figure 3.2) because of the high amount of damagedue to the earthquake and also because of the existence of vegetation areas in the region.

The effect of changes in the scattering characteristics of the resolution cell was shown by (φscat) inequation 3.1. If scattering characteristics of a resolution cell are exactly the same for both acquisitionthen (φscat=0). However, φscat is not zero in practice because of two reasons. Firstly, when thetemporal baseline is too high, the land surface changes its scattering characteristics and causes temporaldecorrelation. Secondly, due to the different looking angle the reflection of the resolution cell differs andcauses the geometrical decorrelation.

3.2.3 Main limitations of conventional InSAR

Based on the discussion of the last section, the main limitations of the conventional InSAR method fordeformation monitoring can be listed as:

1. Temporal decorrelation: The change in the reflection characteristics of the earth’s surface within aresolution cell results in temporal decorrelation. This effect makes the InSAR measurements unfeasiblein vegetated areas and in other areas where the scattering characteristics or the positions of the scatterschange in time within a resolution cell.



2. Geometrical decorrelation: The different viewing angles from the two platforms (due to the non-zeroperpendicular baseline) to the same resolution cell on the ground cause a spectral shift in the observationand introduce a noise defined as geometric decorrelation. This effect limits the number of image pairssuitable for interferometric application, and keeps one from fully exploiting the available datasets [33].

3. Atmospheric inhomogeneities: The spatially and temporally variable state of the atmosphere superim-poses a new error signal that infers with the deformation signal. Atmospheric disturbances can stronglycompromise the accuracy of the deformation monitoring.

In addition to these main limitations, the interferograms are affected by two kinds of ambiguities. Firstly, phasedifferences are given in fractions of cycles (all pixels have a phase between 0 and 1), not as integer numbersof cycles. Secondly, interferograms provide a relative phase change, no absolute changes. This means that itis necessary to know a point with null deformation and refer all measurements to it.

3.3 Persistent Scatterer InSAR

In this section the Persistent Scatterer technique, also known as PS-InSAR will be explained. First there willbe a subsection that deals with the basic concepts of this technique. The second part deals with the mainissues of interpreting the PS-InSAR results.

3.3.1 Concept of PS-InSAR

The PS-InSAR technique is an advanced InSAR technique that has been developed to overcome the mainlimitations of conventional InSAR. These limitations are all caused by the lack of coherence in images due tothe geometric and temporal decorrelation and atmospheric effects: the PS-InSAR technique aims at findingsome features in the radar images that remain coherent over long time intervals, hereafter called PersistentScatterers (PSs). In other words, PSs are isolated points with constant backscatter characteristics in time, sothe φscat is comparable for these points. The PS-InSAR technique is a multi-interferogram technique whichuses an extensive archive of satellite radar data to find these isolated points that are coherent in all radarimages. Figure F.7 shows the detected PSs in the Harlingen area in the Netherlands. The color of the pointsrepresents the deformation velocity for each PS.

The first advantage of PS-InSAR is that temporal and geometrical decorrelations are minimal in this technique.Due to the stable phase behavior of PSs in time, temporal decorrelation becomes minimal in PS-InSAR. Fur-thermore, because of the small dimension of PSs with respect to the resolution cell, geometrical decorrelationis also minimal, which leads to good coherence even for interferogram pairs with a large perpendicular baseline.Therefore, all available images can be exploited for interferometric analysis.

Another advantage of PS-InSAR is that the used different interferograms allow us to estimate the atmosphericphase and to remove this effect from the final results. Based on different temporal and spatial behavior, thecontribution of topography, deformation and atmosphere can be estimated and separated from each other.Topography is not dependent on time, but scales linearly with the perpendicular baseline. Deformation isindependent of the baseline, but is correlated in time. Atmosphere is independent of baseline, uncorrelated intime, but spatially correlated per interferogram [36].

The PS scatterers are usually small features (small with respect to the pixel size) with a dominant reflectionin a resolution cell. Figure 3.3 shows the difference between the distributed scattering pixel and the pixelwith dominant scatterer (or PS), and shows the different phase behavior for different resolution cells. Most ofPSs are man made features, so there is a high density of them in urban areas and on infrastructures such asbridges, roads, dams and dikes. Also in mountain areas, some rocks and boulders can play the role of naturalPSs.


3.3. PERSISTENT SCATTERER INSAR 27

Figure 3.3: Different scattering resolution cell

The final result of the PS-InSAR technique, after removing the atmospheric effect, is a deformation time seriesfor each PS. An important characteristic of these time series is that it shows the PS deformation in all imageswith respect to the master image (time reference). Also, the deformation of the PS is relative to the referencepoint. (This reference point is chosen in an image with the assumption of zero deformation). Using thesetime series it is possible to model the deformation behavior during time. Figure 3.4 shows these time seriesfor one PS and the estimated linear deformation model for this point. Using a linear model, it is possible toestimate the velocity of deformation (the slope of the linear model).

Summarizing: By using all available images and removing the atmospheric signal, the PS-InSAR techniquetakes conventional InSAR one step further to derive relatively precise displacement and velocity estimation atspecific points on the ground with an accuracy of 1 mm/year.

3.3.2 Main issues in interpretation of PS-InSAR results

Efficient use of the PS-InSAR technique for deformation monitoring depends on a correct interpretation of itsresults. However, there are a lot of different factors which should be considered in this interpretation. Thissection will summarize some of the main issues related to the interpretation of the estimated deformationusing PS-InSAR.

Location of PSs: The interpretation of PS-InSAR data is dealing with the opportunistic nature of this tech-nique. This means that the number and location of persistent scatters can not be predicted or optimizedbeforehand as they depend on the dielectric properties of the target materials and the geometry of thesurfaces in relation to the satellite. So, it makes it difficult to define which specific features or defor-mation phenomena will be monitored. For example, the pixel size for ERS-1 images is 20x4 meters.The detected deformation in such an area could be due to the different features. Interpretation of theestimated deformation usually requires defining a scatterer object in the resolution cell.

Deformation in LOS direction: All deformations measured with PS-InSAR are projections of the real defor-mation in the LOS direction of the radar satellite. So, it is not possible to decompose this deformationinto the North, East, or Up deformation. However, using more than one observation (e.g. deformationfrom both ascending and descending track), it is possible to decompose this measured deformation into



Figure 3.4: Example of time series

the interesting deformation parameters in other directions. The detail of deformation decomposition canbe found in section 4.3 about inverse modeling.

PS selection: The possible errors in the PS detection procedure are another topic that should be consideredin the interpretation of the final results of PS-InSAR. The detected PSs are points that passed thetesting procedure in PS processing. Therefore two kind of errors are distinguished:

1. Type-I error: These points are the coherent points that are rejected and have not been detected asPS, whereas they should have been accepted. These errors are usually because of high deformationrate or significant nonlinearity in deformation.

2. Type-II error: These points are incoherent radar targets that show, by coincidence, a high coher-ence and are detected as PS. These are falsely accepted points. They are usually isolated pointswith high estimated deformation rate and without side lobes.

For the interpretation of the results, the type-I error is not a problem. Only, it should be considered thatthere may be undetected nonlinear or large deformation in the area. However, type-II errors should befound as outliers and should be removed from the final results.

Reference point: The reference point is the point within the study area to which all deformation measure-ments are relative. Therefore, if the absolute deformation of points is needed, it is important that thereference point itself is not moving over time. However, in many applications we are interested in onlyrelative deformation in the study area and instability of the reference point does not cause any prob-lem. It should be considered during the interpretation of the results that all estimated deformations arerelative to this point.

Side lobes: Due to the sinc pattern of the reflected radar wave, usually the neighboring pixels of a PS arealso affected by PS reflection and are detected as PS. So, there are some imaginary PSs that are not realobjects. These pixels are around the real PS pixel. These imaginary PSs are called side lobes. Since theamplitude of the reflected wave of the side lobes is smaller than the PS’s main lobe, these points can befiltered based on their amplitude. However, the estimated deformation for side lobes is the same as thedeformation of the PS’s main lobe. So, they are no problem in the deformation monitoring application.


3.3. PERSISTENT SCATTERER INSAR 29

Figure 3.5: Possible deformation for buildings

The only thing that should be considered is that all these points correspond to one PS and they are notseparate PSs.

High displacement rate (phase unwrapping): The derived deformation rate with the PS-InSAR techniqueis in the direction of the satellite’s LOS. A measurement of a displacement in the LOS direction islimited to a fraction of the radar wavelength. This means that the PS technique is, just like conventionalinterferometry, only able to measure the wrapped part of the phase shift in the range of -λ/2 to +λ/2(e.g. for wavelength of 28 mm, it means -14 mm to 14 mm). With PS-InSAR, this ambiguity is solvedusing phase unwrapping methods that calculate the correct number of phase cycles. These need to beadded to each wrapped phase measurement. However in areas with a deformation rate where more thanone phase cycle of displacement has occurred between two acquisitions, the phase unwrapping may fail.So, in such an area the estimated deformation rate is inaccurate. This implies that large deformationcomponents can not be measured properly with this technique.

Significantly non-linear motion: The detection and identification of PSs is dependent on rather conservativetypes of deformation such as linear deformation [35]. In the case of significant non-linear motion, theemployed algorithm may average out this deformation. So, an isolated coherent target that exhibitsa complicated deformation pattern may not be identified. Generally, it is necessary that the linearityassumption for deformation mechanism is valid for a particular area during sampling time. Otherwise,some existing deformation will not be detected and the detected deformations also become incorrectand unreliable.

Autonomous movements: A PS-InSAR measurement might be of good accuracy, but is not in fact relatedto the expected deformation mechanisms. It may be autonomous deformation of one PS, for exampleone building in the area. Figure 3.5 shows some possible deformations of a building and its surrounding.In case A the building undergoes an autonomous movement with respect to its surrounding due to a badfoundation. Case B and C show a deformation of the surroundings due to compaction or gas extraction.

In PS-InSAR applications that try to detect the deformation of particular buildings, these autonomousmovements are no difficulty in the deformation interpretation. However, when the objective of PS-InSAR in a particular application is the detection of spatial deformation such as subsidence due to gasextraction, these autonomous movements should be detected and excluded from the collection of PSswhich have deformation due to subsidence.

Figure 3.6 shows another example of an autonomous movement. A house rolls over due to its inap-propriate foundation and compaction of the ground underneath it. Because of its close distance to thedike, the detected deformation may be interpreted as dike deformation. However, it is an autonomousmovement of the dike and is not related to the interested deformation, which can be subsidence of thedike for example.

Quality of results: The quality assessment of the PS-InSAR is still a research question. Generally, with perfectconditions, the relative LOS precision for the deformation rate can reach sub-millimeters. However, thereare a lot of variable factors which affect the final quality of estimated deformation rate and can affect thefinal interpretation also. Some of these factors are: the temporal distribution of SAR data, the number



Figure 3.6: Autonomous movement due to settlement

of used images, the spatial distribution and characteristics of the target, the land cover characteristics,the rate of deformation, the linearity of deformation, the validity of reference point, the distance of themeasurement from the reference point, the uncompensated topography and the atmospheric artifacts,etc.

Considering all these factors reveals that the overall quality assessment for PS-InSAR is not a straightforward task and requires an in-depth understanding of these issues. These parameters are variablefor different areas and different deformation mechanisms. More details about the quality of the dikemonitoring results can be found in chapter 5.


Chapter 4

Estimation of dike deformationparameters

In this chapter the PS-InSAR technique and the application to measure deformation of dikes come together.A deformation normally has components in North, East and Up-direction. However, radar only measures thedeformation in the direction of the radar LOS. In general there are two approaches to solve the unknowncomponents of the deformation; namely forward and inverse modeling. Inverse modeling solves the unknownsbased on the available measurements. Forward modeling determines how the radar observations will look like,when the deformation is given. Both techniques are introduced and discussed in this chapter. Before the usedmodels are presented, the first section treats the question which deformation mechanisms can be detectedthat cause the measured deformation. Some cannot be detected at all, for others the probability of detectionmight be low. This determines which deformation mechanisms are actually modeled. The second section isabout the application of forward modeling, followed by inverse modeling.

4.1 Detection of deformation mechanisms with PS-InSAR

Although radar is very suitable for deformation detection, not all deformation caused by the different dikedeformation mechanisms can be detected. Also, for some deformation mechanisms the probability of detectionis low. This section discusses for all deformation mechanisms whether they can be detected with the PS-InSARtechnique or not. To decide which kinds of deformation can be detected, the temporal and spatial behaviorof the underlying mechanisms, see section 2.2 and the characteristics of the data acquisition, e.g. the revisitperiod of the satellite, have to be taken into account.

4.1.1 Discussion of detectability of deformation mechanisms

For this discussion it is assumed that there are PSs, on one or both sides of the dike. Without this assumptionthere might be no detection and classification possible at all. The fact that there are PSs implies that thedeformation will be detected. It makes sense that a large scale phenomenon, i.e. strong spatial correlation, iseasier to detect than a small scale phenomenon, i.e. no spatial correlation. This is because of the fact that theprobability that there is a PS, influenced by the deformation mechanism, is larger for a large scale phenomenon.So, a strong spatial correlation increases the probability of detection. This probability determines whether itmakes sense to model a certain deformation mechanism or not. Table 4.1 summarizes the results of thisdiscussion.

31

32 CHAPTER 4. ESTIMATION OF DIKE DEFORMATION PARAMETERS

Deformation mechanism DetectableDeformation due to a precursor sliding YesDeformation due to a precursor sliding of the inner slope YesDeformation due to a precursor sliding of the outer slope YesDeformation due to erosion of the top and inner slope NoDeformation due to erosion of the outer slope NoDeformation due to erosion of the foreland NoDeformation due to piping NoDeformation due to seepage YesDeformation due to sliding of the protective cover YesHorizontal deformation of a dike YesSettlement YesSubsidence YesSwelling Yes

Table 4.1: Deformation mechanisms potentially detectable with PS-InSAR.

Deformation due to a precursor sliding: Sliding of the whole dike results in large deformation (meter level)in a short time period. This deformation is very large with respect to the radar wavelength. Becauseof unwrapping problems and temporal decorrelation, the probability of detection is very small, assumingthat the coherence is the same. Here, the influence of the spatial correlation is not taken into account.The probability of detection becomes larger for a spatially correlated signal. However, sliding announcesitself by a small elastic and plastic deformation in the horizontal and vertical plane. Note that thisonly holds true for peat dikes. The fact that there is some spatial correlation makes the probability ofdetection of these kinds of deformation likely. This probability also increases when this effect can bemeasured on both sides of the dike.

Deformation due to a precursor sliding of the inner slope: Also a sliding of the inner slope results in alarge deformation (meter level) in a very short time period. Because of the same reasons as for de-formation due to a precursor sliding, the probability of detection of these kinds of deformation is verylow. However, normally this process announces itself by a small deformation over a certain time period,which might be a couple of years. The fact that there is some spatial correlation makes the probabilityof the detection of these kinds of deformation high. The assumption that there are PSs on the innerside of the dike, might be a problem when the slope is fully covered with grass, which is mostly the casefor the inner slope.

Deformation due to a precursor sliding of the outer slope: Sliding of the outer slope is in fact the sameprocess as sliding of the inner slope, only this process takes place at the other side of the dike. Usingthe same argumentation, it can be stated that the detection of these kinds of deformation has a highprobability.

Deformation due to erosion of the top and inner slope: Erosion of the top and the inner slope of the dikeis a local process, so the spatial correlation is low. When the inner side and the top of the dike are fullycovered with grass, which is the case most of the times, this deformation is hardly detectable becauseof the low amount of PSs there, i.e. vegetation has a bad coherence. Only when there is an objecton the dike that gives a good reflection, the deformation can be seen. Also these kinds of deformationare due to extreme circumstances, like overflowing and wave overtopping. Normally, this only happenswhen there is a high water level in combination with a strong wind. It is common practice to inspectthe dikes after such circumstances, so the damage will be detected and repaired if necessary as soon aspossible. A possible detection can be seen as a jump or a loss of coherence in the time series. When thedeformation is large with respect to the radar’s wavelength, the probability of detection becomes verysmall due to a possible unwrapping error. Concluding, it can be said, that this deformation mechanismmight be detected, but the probability of detection is low.

Deformation due to erosion of the outer slope: The difficulties with the detection of erosion of the outerslope are more or less covered in the discussion about the erosion of the inner slope. But also another


4.1. DETECTION OF DEFORMATION MECHANISMS WITH PS-INSAR 33

effect is important: the erosion of the outer slope is likely to be under water, so it is not detectable withradar anyhow.

Deformation due to erosion of the foreland: Erosion of the foreland takes place below water level most ofthe time, so it cannot be detected with radar at all.

Deformation due to piping: Deformation due to piping is a very local effect, which causes holes in the landclose to the dike. When there is a PS in or close to this hole it may be detected. However, the factthat this deformation is spatially uncorrelated and that the probability that a PS coincides with a holeis low, gives a low probability in the detection of deformation due to piping.

Deformation due to seepage: Seepage can theoretically be measured with radar. A high water level overa longer time period will push the ground water table behind the dike upwards, which may result in asmall elastic uplift of the land behind the dike. When the water level gets back to its normal level, theland gets also back to its normal state. This can be seen as an outlier in the time series. Notice thatnormally these periods of a high water level are maximally a few weeks. A revisit period of 35 daysreduces the probability of detection.

Deformation due to sliding of the protective cover: Sliding of the protective cover is mostly a relativelyslow process over a stretch of dike. The fact that there is some spatial correlation, gives a high probabilityof detection for this kind of deformation.

Horizontal deformation of a dike: A horizontal deformation of a dike can have several causes. First, thereis a deformation due to a high water level which causes a more or less elastic, horizontal deformationof a dike stretch. However, a small plastic deformation is not excluded. Also nipping ice can cause ahorizontal deformation for a stretch of dike, but this is only true for small dikes. The elastic deformationwill look like an outlier in the time series. However, these kinds of deformation can be large with respectto the radar wavelength, which makes the probability of detection very low. Normally a high water levelis just a few weeks, while the revisit period of the satellite is five weeks. This will also decrease theprobability of detection. The plastic deformation has a high probability to be measurable with radar.First of all the effect is measurable on both sides of the dike, secondly there is spatial correlation.

Settlement: Settlement is a process that occurs on the whole dike and even on the land behind the dike andon the outer foreland. Partly, the deformation is due to compaction of the dike itself, partly because ofcompaction of the underneath soil layers. The magnitude of settlement depends on the age of the dike.When the dike becomes older, the settlement becomes less. The fact that this effect can be measured onboth sides of the dikes, in combination with the spatial and temporal correlation gives a high probabilityin detecting these kinds of deformation.

Subsidence: Subsidence is usually a spatially and temporally correlated phenomenon, which covers a wholearea, so not only the dikes. Many studies have proven that this type of deformation is quite wellmeasurable with radar, see for instance [44], [52] and [61].

Swelling: In the case of swelling, the dike becomes saturated with water due to rain or a high water level. Thismay results in deformation of the whole dike or only one side of the dike. The fact that this effect canbe measured on both sides of the dikes, in combination with the spatial correlation makes the detectionof these kinds of deformation likely.

4.1.2 Superposition of deformation mechanisms

The interpretation of the detected deformation becomes more difficult when there are more than one deforma-tion mechanisms acting on the dike. The PS displacement is in this case a superposition of displacements dueto different deformation mechanisms. In practice, this is not unlikely; a new built dike has always deformationdue to settlement. But at the same time it is possible that there is also a deformation due to a high water level,or deformation due to seepage. However to show the effect of each deformation mechanism, the developedmodels assume only one cause of deformation.



4.2 Forward modeling

Most models in real life applications contain more unknowns than observations, which implies that the systemis not solvable. One method to deal with this situation is forward modeling, which will be discussed in thissection. It starts with an introduction of the concepts of forward modeling. Some general considerations aremade about forward modeling with respect to inverse modeling. After that the model definition and the generalinput parameters are described, even as the developed models for the relevant deformation mechanisms, asidentified in section 4.1, are discussed.

4.2.1 General considerations about forward modeling

In general, with forward modeling one tries to determine what a given sensor would measure in a givenformation and environment. Generally, this is done by applying a set of theoretical equations to the sensorresponse. This set of theoretical equations (the forward models) can be 1D, 2D or 3D. The more complex thegeometry, the more factors can be modeled, but the longer the computing time will be.

In the case of the detection of dike deformation, the sensor is the radar and the forward models are thefeasible deformation mechanisms. In chapter 3 it is stated that the radar cannot measure the full deformationvector, which contains the deformation in the North (Y), East (X) and Up (Z) direction. It only measures thedeformation in the radar LOS. This means that with inverse modeling some assumptions about the directionof the deformation have to be made. Another option could be that forward modeling is used to determine thefull deformation vector. Forward modeling also requires assumptions, for instance on the validity of the usedmodel for a particular situation. Another important question is whether the models are a good description ofthe reality.

4.2.2 General input parameters

In this section the used simple model and the general parameters are described.

Figure 4.1: A dike body’s cross-section of the used model.

For the discussion of the different models, a very simple model is specified that represents a dike. Figure 4.1shows a cross section of this model. The slopes are specified by γ, the base width of the dike is specified by l

(in meters) and the crest height of the dike by h (in meters). The three general parameters are the directionof the length axis of the dike, the heading of the satellite and the incidence angle, each of them will be brieflyexplained.

Direction of the length axis of the dike: The orientation of the length axis of the dike determines its sen-sitivity for the radar LOS deformation. Assume for instance that the orientation of the length axis ofa dike is perpendicular to the satellite’s orbit. Now the radar is not sensitive for a deformation in the


4.2. FORWARD MODELING 35

direction parallel to this orbit, because the radar LOS vector is perpendicular to the direction of themovement.

Heading of the satellite: The heading of the satellite is specified as the azimuth (αh). This parameterspecifies whether the satellite is in an ascending or a descending orbit. Assume that a dike lies parallelto the orbit of an ascending satellite. A deformation away from the satellite perpendicular to this orbitis than seen as a motion towards the satellite in a descending orbit. In other words, the sign of thedeformation is reversed, see figure 4.2.

Incidence angle: The other parameter related to the satellite is the incidence angle (θ). The incidence angleis the angle between the radar beam incident on a surface and the line perpendicular to the local verticalof the ellipsoid, see figure 4.2.

Figure 4.2: A deformation away from a satellite in an ascending orbit perpendicular to this orbit, is seen as amotion towards a satellite in a descending orbit. The dashed line illustrates the dike after deformation. It canbe clearly seen that the distance from the earth to the satellite is increased for an ascending satellite while itis decreased for a descending satellite.

4.2.3 Modeling of deformation mechanisms

In this section the different models of the relevant deformation mechanisms will be presented. First some gen-eral considerations about the way of modeling are discussed, followed by a description of the input parameters.

Deformation due to a precursor sliding: One of the indicators of a precursor sliding is compaction of thedike in combination with an elastic horizontal displacement. For the compaction of the dike the samemodel is used as for settlement. For the horizontal deformation the same model is used as for thehorizontal deformation of a dike. The deformation due to a precursor sliding is a combination of thosetwo processes. The deformation magnitude can be specified by the use of two parameters. The firstparameter dz top (see figure 4.3), specifies the deformation of the crest of the dike in the verticaldirection. Notice that the deformation magnitude is maximal at the top and zero at the foot of the dike.For every point between those points a linear relationship is assumed. The second parameter dx top

(see figure 4.3), specifies the deformation of the crest of the dike in horizontal direction. Also herethe deformation magnitude is maximal at the top and zero at the foot of the dike. For every locationbetween those points a linear relationship is assumed.

Deformation due to a precursor sliding of the inner slope: Deformation due to a precursor sliding of theinner slope has components in the vertical direction and in the direction perpendicular to the length-axisof the dike. It is assumed that the length of the deformation vector is the same over the full width of



Figure 4.3: Model of a deformation due to sliding.

the inner slope. However, the decomposition into two components depends on the distance to the topof the dike. In figure 4.4 this decomposition is visualized. Here α is the parameter that depends on thedistance to the dike’s length axis. A point on the crest of the dike only deforms in the vertical direction(α = 90), a point on the foot of the dike only deforms in the direction perpendicular to the length-axisof the dike (α = 0). The deformation magnitude can be specified by the use of the parameter dSlope

which is the deformation vector parallel to the slope, (see figure 4.4). How this will look in practice isvisualized in figure 4.5.

Figure 4.4: The decomposition of the deformation vector.

Figure 4.5: Model of a deformation due to sliding of the inner slope.

Deformation due to a precursor sliding of the outer slope: This type of deformation mechanism uses thesame model as the one that is used for the sliding of the inner slope of the dike. The only differenceis that the process takes place at the outer side of the dike. Figure 4.6 visualizes how this type ofdeformation is modeled.

Deformation due to seepage: When the water level is high, water pressure can cause seeping of water underthe dike. This may cause an uplift of the land behind the dike. It is assumed that the uplift is the samefor the whole area behind the dike. The deformation magnitude can be specified by the parameterdz foreland (see figure 4.7), which specifies the uplift of the land behind the dike.

Deformation due to sliding of the protective cover: The sliding of the protective cover is modeled as adeformation along the slope of the dike. Because of the fact that the inner slope of the dike is mostlycovered by grass, the model assumes this kind deformation only at the outer slope of the dike. A


4.2. FORWARD MODELING 37

Figure 4.6: Model of a deformation due to sliding of the outer slope of the dike.

Figure 4.7: Model of a deformation due to seepage.

deformation along the slope has components in the vertical direction and in the direction perpendicularto the length-axis of the dike. The magnitude of these components depends on the slope angle of thedike. The deformation magnitude can be specified by the use of the parameter dSlope which is thedeformation vector parallel to the slope. How this will look in practice is visualized in figure 4.8.

Figure 4.8: Model of a deformation due to sliding of the protective cover.

Horizontal deformation of a dike: To model this kind of deformation, the assumption is made that theamount of deformation of a certain point only depends on the height of the dike. This implies thatthe maximum amount of deformation can be found at the crest of the dike. At the foot of the dike,there is no deformation at all. For every point between those points a linear relationship is assumed.Another assumption is that there is only deformation in the direction perpendicular to the length-axis ofthe dike. Figure 4.9 shows the consequence of this way of modeling, i.e. only the steepness of the innerand outer slope changes. The inner slope becomes steeper, while the outer slope becomes less steep.The deformation magnitude can be specified by the parameter dx top (see figure 4.9), which specifiesthe deformation of the crest of the dike in horizontal direction.

Settlement: Settlement results in two different kinds of deformation. First, there is a deformation due toa compaction of the dike itself. Secondly, there is a deformation due to a compaction of the layerunderneath. Here it is assumed that the compaction of the dike itself, for a certain point, only dependson the height of the dike for that particular point. This means that this deformation is maximal at



Figure 4.9: Model of a deformation due to horizontal deformation.

the top and zero at the foot of the dike. For every point between those points a linear relationship isassumed. Then there is a deformation due to compaction of the soil layer underneath the dike. Thetotal deformation is the sum of these two independent components, and its magnitude can be specifiedby the parameters dz top and dz base (see figure 4.10).

Figure 4.10: Model of a deformation due to settlement.

Subsidence: In case of subsidence not only the dike will deform, but also the surrounding area. In the modelit is assumed that the deformation magnitude of the dike and the surrounding area is the same andthat there is only deformation in the z-direction. The deformation magnitude can be specified by theparameter dz sub (see Figure 4.11), which specifies the deformation of the top of the dike in z-direction.

Figure 4.11: Model of a deformation due to subsidence.

Swelling: In the case of swelling, the deformation rate can be different for each part of the dike. However,one assumption is that the direction of the deformation is perpendicular to the dike. This means that adeformation of the crest of the dike has only a component in the z-direction. A point on the slope ofthe dike has a component in the x- and z-direction. In the example, the deformation due to swelling islargest for the outer side of the dike, see figure 4.12. The deformation magnitude can be specified forthe inner slope (dinner slope), the top (dtop) and the outer slope of the dike (douter slope).

With these models it is possible to calculate the radar LOS, for different heading directions and orien-tations of the dike. Here equation 4.1 can be used, because all terms are known. This results in a map,


4.3. INVERSE MODELING 39

Figure 4.12: Model of a deformation due to swelling.

where each grid cell represents a PS. The colors indicate the magnitude of the deformation in the radarLOS.

4.3 Inverse modeling

The goal of inverse modeling is to derive deformation parameters from the observations. So, first the PS-InSAR observations and interesting deformation parameters are defined. After that, the mathematical modelfor inverse modeling is described.

Observations: The PS-InSAR observations are deformation rates in the LOS direction of the satellite. Basedon different satellite orbits, there are two kind of observations: observations from ascending orbits, andobservations from descending orbits. But instead of using only the estimated linear deformation ratesas observations, also all measurements which created the time series of the PSs can be considered asthe observations.

The main parameters to define these observations, i.e. to define the LOS direction for each observation,are the incident angle and the satellite heading (azimuth). Figure 4.13 shows these two parameters forboth ascending and descending observations.

Deformation parameters: The interesting deformation parameters are defined as three deformation compo-nents in three directions with respect to a dike. Figure 4.14) shows these three components in the dikecoordinate system.

dy: deformation component in the length axis of a dike

dx: deformation component perpendicular to the length axis of a dike

dz: deformation component in up direction (dz=du)

An important parameter to define the orientation of the above components with respect to the geo-graphical coordinate system (North, East, Up), is the azimuth of the length axis of a dike. Figure 4.14also shows the relation between the dike coordinate system and the geographical coordinate system.

Now, with these observations and deformation parameters, the inverse modeling problem becomes the decom-position of the observed LOS deformation to the dx, dy, and dz components.

As PS-InSAR observations are only sensitive to the deformation towards or away from the satellite in LOSdirection, the observed deformation implies a non-uniqueness. That is, the observations are only the projectionof the 3D deformation vector, with the components (dn, de, du) in north, east, and up direction respectively,to one LOS component (dr) (see figure 4.15) The deformation in the LOS can be calculated with equation 4.1[37]:



Figure 4.13: The observation geometry A) Heading of ascending orbit, B) Heading of the descending orbit,C) Incidence angle for ascending orbit, D) Incidence angle for descending orbit

Figure 4.14: A) Dike coordinate system, B) Relation of dike coordinate system and geographical coordinatesystem.



Figure 4.15: Deformation components

dr = du cos θ − sin θ

[

dn(cos(αh −3π

2) + de sin(αh −

3π

2)

]

(4.1)

Where:θ incidence angleαh satellite headingdr observed deformation in range direction (LOS)du deformation in Up directiondn deformation in North directionde deformation in East direction

Because of the projection of the 3D deformation vector to the LOS deformation, it is not possible to decomposethe observed deformation to the north, east, and up components. Even when using two observations, com-position of ascending and descending observations, it is possible to derive only two out of three components(two observation and two unknowns). To be able to retrieve all of the three components, some assumptionsabout one or two components are necessary, based on some prior knowledge about the characteristics of theexpected deformation mechanisms.

Below, three cases of possible observations are considered. For each case, the system of observation equationsfor the inverse modeling is developed, followed by a discussion about the possible assumptions that should bemade.

Case 1: Only one observation (ascending or descending): We first consider the case that only one ob-servation is available (ascending or descending). In this case it is possible to assume no horizontaldeformation and project the observed deformation in LOS into the vertical component. However, this isnot a very realistic assumption for some deformation mechanisms. Therefore, the use of this assumptionneeds more prior knowledge about the expected deformation. For example, in the case of subsidence, it islikely that there is no horizontal deformation, so the observed deformation is only because of the verticaldeformation (dz). Then the second term of equation 4.1 becomes zero. In this case, the observationequation for inverse modeling becomes:

dr = cos θdu (4.2)

Case 2: Two observations (ascending and descending): In this case, we consider that both ascending ordescending observations are available. To derive the three deformation components from only these two



observations, an assumption on one of the three components is necessary. In dike monitoring, as thedeformation in the length direction of the dike is not very likely, it is possible to assume zero deformationin this direction (dy=0). With this assumption, it is possible to derive dx and dz from the ascendingand descending observations.

In order to use equation 4.1 for inverse modeling, it is necessary to transform the deformation in Northand East directions into the horizontal deformation parameters(dx and dy). Using the rotation withrotation angle the azimuth of the dike, we have:

(

de

dn

)

=

(

cos γa sin γa

− sin γa cos γa

) (

dx

dy

)

(4.3)

Where:dx deformation perpendicular to the lenght direction of dikesdy deformation in the lenght direction of dikesγa azimuth of lenght axis of dike

Using the assumption that dy=0, equation 4.3 becomes:

(

de

dn

)

=

(

cos γa

sin(−γa)

)

dx (4.4)

Substitution of 4.4 into 4.1 and using some verification, we have:

dr = du cos θ − dx sin θ cos(αh − γa) (4.5)

Using equation 4.5 for both ascending and decending observations, we can write the system of observationequations as:

(

dasc

ddesc

)

=

(

cos θ − sin θ(αha − γa)cos θ − sin θ(αhd − γa)

)

(4.6)

Where:dasc observed deformation in ascending trackddesc observed deformation in descending trackαha heading of ascending orbitαhd heading of descending orbit

Assuming independent observations, it is possible to write 4.6 as the Gauss-Markov model:

E{y} = Ax; Dy = Qyy (4.7)

Where:

A =

(


)

, Qyy =

(

σ2desc 00 σ2

desc

)

, x =

(

du

dx

)

Finally, the solution of 4.7 gives the estimated deformation parameters (dx and dz) for each PS-InSARpoint:

x = (AT Q−1

yy A)−1AT Q−1

yy y Qxx = (AT QyyA)−1 (4.8)

Case 3: More observations (ascending and descending for different points): In last case, the observa-tion equation for only two observations was derived. Despite the fact that there are only two possibleobservations for each PS, with some assumption about the spatial behavior of the expected deformationmechanisms, it is possible to use more observations for the estimation of the deformation parameters.Using more observations will also increase the accuracy of the final estimation of the parameters.

Lets assume homogeneous deformation mechanisms. This means that the deformation parameters arethe same for the whole, or some interesting part of the dike. Then the unknown parameters (dx and dz)



for all PSs on that part of the dike become the same, while we can use all observations of these PSs inour system of observation equations:

E{

dasc1dasc2

.

.

dascm

ddasc1ddasc2

.

ddascn

} =

cos θ − sin θ(αha − γa).

.

.


.

.

cos θ − sin θ(αhd − γa)

(

dz

dx

)

D{y} =

σ2dasc1

σ2

dasc2

.

.

σ2

dascm

σ2

ddesc1

σ2ddesc2

.

σ2

dascn

(4.9)

The solution of the equation 4.9 is (using Best Linear Unbiased Estimation (BLUE)):

x = (AT Q−1

yy A)−1AT Q−1

yy y Qxx = (AT QyyA)−1 (4.10)

Where:x BLUE of the unknown parametersQxx variance covariance matrix of the BLUE

Sensitivity of observations to different deformation components: As can be seen in equation 4.10, thefinal precision of the estimated deformation parameters is dependent on the radar acquisition geometrywith respect to the dike (A-matrix) and the precision of the observations (Qyy). The precision of theobservations is already given as the results of the PS processing. However, the A-matrix depends ongeometric parameters such as the incident angle, the heading angles, the number of observations, andthe azimuth of the dike. Therefore for different satellites and different orientations of the dike the finalprecision of the estimated deformation parameters are altered.

Assuming uncorrelated observations, with the same standard deviation, we have:

Qxx = σ2(AT A)−1 (4.11)

The square root of the diagonal terms of Qxx give the standard deviation of the estimated deformationparameters. If the standard deviation of the observations is equal to one, the diagonal terms provide ameasure of the effect of geometry on these estimates in terms of relative measurement error. Figure 4.16shows this sensitivity for different orientations of a dike in the Netherlands for the ERS satellite. Theused parameters in this case are an incidence angle of 23 degrees and a heading of 347 and 193 degreesfor ascending and descending orbits respectively. As we expected, the standard deviation of the dx

component becomes larger when increasing the azimuth of the dike from 0 to 90 degrees. The reasonfor this effect is that the sensitivity to the deformation component in North-South direction, e.g. dx

when the azimuth of the dike is 90 degrees, is weak due to the near polar orbit of the ERS satellite.



Figure 4.16: Sensitivity (standard deviation in mm) of estimated deformation parameters to the dike orien-tation .


Chapter 5

Case study methodology

In this chapter the methodology is presented that was used for conducting the case studies. It starts with adescription of how the case study locations are chosen, followed by an overview of the relevant datasets andtheir proposed expectations. After that some explanation is given about the georeferencing method and thechoice of the reference point. Next some considerations are described about the time series analysis, hypothesistesting and quality assessment. The methodology part ends with a description of the determination of thefeasibility of the results.

5.1 The choice of the case study locations

In this section the choice of the case study locations is discussed. This choice was first limited by the availabilityof the radar data. These data were available for parts of the provinces Groningen, Friesland, Noord-Hollandand Flevoland. From these areas, the locations were chosen where the dikes were visible, mainly focusing onthat dikes that belong to the primary water barriers, i.e. the dikes along the IJsselmeer and the Waddenzee.A closer look at these images already made clear that some interesting features were visible. This resulted inthe following list of potential case study locations:

• The IJsselmeer dikes around the Noord-Oostpolder;

• The dikes around the island of Marken;

• The dikes around the complex of Kornwerderzand;

• The dike near Harlingen;

• The IJsselmeer dikes near Lelystad in Flevoland;

• The dike near Lauwersoog;

• The dike near Delfzijl.

Selection of the case study was based on available data, amount of interesting locations and the time limitationsof the project. Finally the first four case studies where chosen.

45

46 CHAPTER 5. CASE STUDY METHODOLOGY

5.2 Data gathering

The datasets that might be interesting for the analysis of the case studies will be discussed in this section. Amore detailed description of the datasets can be found in Appendix A. The datasets below are listed in theorder of importance.

Radar data This dataset contains an overview of the used images, the Multi Reflectivity Map (MRM), afile with the location, height, deformation and coherence for every PS. Also the time series of theatmospheric residuals and the time series for the non linear movements are included. The MRM is usedto distinguish between the main points and sidelobes. The other files are used to generate the timeseries and calculate the parameters of interest.

Topographical map 1:10.000 The topographic vector map (Top10vector) is used as a topographical back-ground. This map is used for georeferencing of the PSs if no better alternatives where available. It alsoprovides an overview of the area of interest and gives information about objects close to the dikes, thisis used to derive the causes of the reflection.

DTB-wet and DTB-dry The Digital Topographical Files (DTB) of the wet and dry infrastructure at scale1:1000 together form the DTB2000. These datasets contain very detailed and precise information aboutthe geometry of dikes and highways. This makes these datasets very useful for the georeferencing ofthe PSs. It also provides detailed information about the objects on and close to the dike, this is used toderive the causes of reflection.

Validation datasets Validation datasets, for instance leveling, tachymetry or GPS data, can be used tovalidate the PS-InSAR technique.

AHN The estimated heights of the PSs can be used for the georeferencing of the PSs, i.e. to decide whetherthe reflection comes from the top or foot of an object.

Geotechnical profiles These profiles show the structure of the subsurface of the dike and the underlying soillayers. It might be that the measured deformation is related to the soil type below the dikes. Thegeotechnical profiles can be used to verify this hypothesis.

Soil map and borehole measurements Both the soil map (scale 1:50.000) and borehole measurements canbe used as an alternative when no geotechnical profiles are available. The soil map only provides informa-tion about the first meter below the surface, borehole measurements contain very detailed informationabout the subsoil layers, but only for the borehole locations.

Technical drawings Technical drawings of a dike give information about the structure of dike; cross pro-files, information about the used materials, foundation, etc. This information possibly helps with theinterpretation of the PSs.

Aerial photography Available aerial photographs (also accessable from Google-Earth) can be used to get afirst impression of the areas of interest; a first indication what causes the PSs can be given.

Time series ground water levels These time series show the fluctuations in the ground water level for somepoints. It might be that the measured deformation is related to the fluctuations in the ground waterlevel. The time series can be used to verify this hypothesis.

Time series water level IJsselmeer These time series show for some points the fluctuations of the waterlevel in the IJsselmeer. It might be that the measured deformation is related to the fluctuations in waterlevel. The time series can be used to verify this hypothesis.

5.3 Preparation of the data

Before starting the interpretation of the radar data, some preparation steps have to be conducted, namely:the georeferencing and the selection of a new reference point. Both steps will be discussed in this section.


5.4. TIME SERIES ANALYSIS 47

5.3.1 Georeferencing

To determine which object is causing the scattering, it is essential to georeference the PSs. The PSs, whichwhere supplied in the ’Rijksdriehoeks’ (RD) reference system, are shifted with respect to their true locationsbecause of an error in the starting time of the acquisition by the ERS satellite. This shift is the same for all thePSs in one radar image and can be up to hundreds of meters. In a normal georeferencing procedure, groundcontrol points are selected to ensure an accurate georeferencing. Ground control points are geographicalfeatures of known location that are recognizable on images and can be used to determine the geometricalcorrection. However, for this research such ground control points (like corner reflectors) are not available. Thisreduces the accuracy of the georeferencing. In this project, the radar data is georeferenced with respect toa topographical dataset. The procedure for both ascending and descending dataset consists of the followingsteps:

• Selection of coordinates for at least 2 corresponding points in the PSs dataset and the used topographicalbackground map, like the DTB-wet or the Top10vector;

• Calculation of the mean shift in the coordinates between these corresponding points;

• Apply the shift to the PSs.

After this procedure, the standard deviations of the differences between the old coordinates and the transformedcoordinates for the control points are calculated. This standard deviation represents the relative precision ofthe georeferencing. The absolute precision is assumed to be equal to the precision of the used dataset.

5.3.2 Selection of the reference point

The estimated deformation with the PS-InSAR technique is relative with respect to a certain reference point,i.e. a point with a height, deformation rate and residuals equal to zero, and a coherence of one. Theheights, deformation and coherence of all the other points are with respect to this reference point. Thispoint is randomly chosen from a list of points with coherence above a certain threshold. This implies thatthe reference point in an ascending dataset is independent from the reference point in a descending dataset,which makes the interpretation of the combined datasets not straightforward. For a correct interpretationand a correct derivation of the deformation parameters, the reference points have to be redefined. Thereare several possibilities to ensure a straightforward interpretation of the combined ascending and descendingdatasets. First of all, it is possible to choose a stable reference point in both datasets. This method impliesthe availability of ground truth data, but even when it is clear that a certain area is stable, there is a probabilitythat a point is just noise or an autonomous movement. To overcome this problem, not a single reference pointis chosen, but the mean of a number of points in a certain area can be put to zero. Another method is tochoose a point that occurs in both the ascending and descending dataset. However, when this point in realitydeforms horizontally, the interpretation is again not straightforward. Notice that this effect can be seen in thewhole combined dataset, which might be unrealistic. When this is the case, another reference point has to bechosen. In both approaches the values for the deformation rate, heights and residuals of the new referencepoints becomes zero and the coherence one. All other PSs have to be corrected, to make them relative withrespect to the new reference point.

5.4 Time series analysis

In this step, we visualize the deformation time series for each PS point which was detected as deformationin the last step. Some characteristics of these time series are visually analyzed to check the validity of linearmodel, and to check other possibilities for phase unwrapping.



Figure 5.1: Linear model vs. alternative models.

Validity of linear model: The time series are visually checked to see whether the linear model is valid or not.We also check for a possible alternative model for some particular time series. Figure 5.1 shows theexample of time series with a linear model and two alternative models.

Check Phase Unwrapping: We visually verify the other possibilities for phase unwrapping. This means thatwe visualize not only the estimated deformation time series but also these time series with + and -one cycle (in our case 28 mm), to see whether any other possibility for phase unwrapping is likely ornot. Figure 5.2 shows this visualization. In these time series, red points show the results of the currentphase unwrapping solution. Blue and black points respectively show the time series with + 28 mm and- 28 mm. For example, we verify whether the alternative solution for phase unwrapping (dashed line) isfeasible or not.

5.5 Detection of deformation

The goal of this step is to find or detect the PSs on the dike that show deformation. For each PS point,there are four possibilities:

Outliers: These are PSs that contain only noise. These points are the result of type II errors of PSprocessing (3.3.2) which are regarded as coherent points and detected as PS, but actually they arenot. These falsely detected PSs are spatially uncorrelated (isolated points), usually with a highdeformation rate, low coherence and without sidelobes.

Autonomous movements: These points are the results of an autonomous deformation of one PS.These PSs are spatially uncorrelated, usually with sidelobes. Interpretation of these autonomousmovements needs more investigation.

Deformation: The PSs that show spatially correlated behavior on dikes, with absolute deformation ratelarger than 1 mm/year can be classified as deformation areas. These points usually have sidelobes.

Stability: Stable points can be defined as points that have an absolute deformation rate smaller than1 mm/year. These points are usually spatially correlated and have sidelobes.

Based on their spatial behavior (correlation), deformation rate and sidelobes, PSs can be classified toone of these four classes. Outliers are detected based on uncorrelated behavior, high deformation rateand bad coherence. The other three classes can be subdivided in two hypotheses:

Null-hypothesis: point is stable (no deformation)

Alternative hypothesis: the point is not stable.


5.6. CLASSIFICATION OF DEFORMATION 49

Figure 5.2: Other possibilities for phase unwrapping.

If the null-hypothesis is rejected, so the point is not stable, we will test whether the detected deformationis spatially correlated or not. If not there are autonomous movements. In general, the decision betweenautonomous movement and deformation is not very straight forward and needs more consideration. Itis possible that some deformation mechanisms are local deformation and show the same behavior asautonomous movements. Figure 5.3 shows the decision tree for this classification.

5.6 Classification of deformation

The goal of this step is to decide for each detected deformation area which deformation mechanism is feasibleand classify the detected deformation in different deformation mechanisms. The important factors for thisdecision are:

1. Difference in ascending and descending observations (due to the horizontal movements, or deformationin only one side of the dike).

2. Spatial correlation of PSs with points close to the dike. That is, we investigate whether only the pointson dikes show deformation or also the points close to the dike (e.g. for subsidence it is more likely thatthe points close to the dike also show deformation).

3. Magnitude of deformation rate. (different deformation mechanisms have different magnitude)

4. Temporal behavior: From time-series analysis, temporal behavior of the detected deformation can bederived.

5. Deformation direction: using inverse models, it is possible to derive vertical and horizontal deformation.(Only in cases that we have both ascending and descending observation).

Figure 5.4 shows these factors for different deformation mechanism. Based on their difference in these factors,PSs can be classified to different mechanisms. Figure 5.5 shows the decision tree for this classification in the



Figure 5.3: Decision tree for deformation detection.

Figure 5.4: Characteristics of deformation mechanisms.


5.7. QUALITY ASSESSMENT 51

Figure 5.5: Decision tree deformation classification: two observations

Figure 5.6: Decision tree deformation classification: one observation

case that both ascending and descending observations are available. In the situation that only one kind ofobservation (ascending or descending) is available, with assumption that horizontal deformation is zero, wecan classify the detected deformation (see figure 5.6).

In addition to these factors, which are only based on radar observations, there is also other information.Examples of these kinds of information are: soil maps, technical drawings of dikes, water levels, etc. Thesecan also be used to interpret the detected deformation and to assign it to one of the deformation mechanisms.

5.7 Quality assessment

Quality as defined in geodesy is divided into internal and external precision and internal and external reliability.The internal precision says something about the dispersion of the estimated measurements, while the externalprecision is the dispersion of the estimated unknown parameters. Internal reliability is a measure of the model



error that can be detected with a certain probability, whereas the external reliability is defined as the influence ofthis model error on the estimated unknown parameters. Precision and reliability are independent componentsof the quality description. A high precision of the measurements does not imply a reliable estimation of theunknown parameters and vice versa. Because of the fact that the time series cover a long time span, even withlarge noise in the observations, it is easy to obtain a deformation rate with a high precision, assuming thatthe deformation is linear over time. However, this assumption is not necessarily true and has to be checkedwith hypothesis testing, which is a reliability aspect. The temporal distribution of the measurements andspatial distribution of the PSs are regarded as deterministic quantities. Also the ambiguities are assumed tobe known and deterministic. In this section the internal and external precision are discussed. For this projectthe reliability of the linear model is tested with the Global Overall Model test. This is described at the end ofthis section.

5.7.1 Internal precision

The internal precision describes the dispersion of the estimated measurements. This is calculated using thepropagation law of the variances.

Where Qxx is given by:Qyy = AQxxAT (5.1)

Qxx = (AT Q−1

yy A)−1 (5.2)

Where:

A = The design matrixQyy = The variance-covariance matrix of the estimated observationsQyy = The variance-covariance matrix of the observationsQxx = The variance-covariance matrix of the estimators

In the case of this project, the observations are not the raw observations, as they are acquired by the satellite.Here, the time series for all the PSs, i.e. the deformation for different epochs with respect to t = 0, is regardedas the observations, collected in the measurement vector y, with D(y)= 42 × Im mm2. For corner reflectors

the variance equals 22 (see [43]). However for natural scatterers this value is larger, here we choose 42.

Based on these observations, the deformation rate is estimated. In that case, the design matrix A, is given as:A = (t1 ... tm)T , assuming that for t = 0, the deformation is also zero. The estimated deformation rates areused to derive the deformation parameters dx and dz, see section 4.3 on inverse modeling.

When the variances of the estimated deformation rates vi are given by σ2vi

,Qyy becomes a diagonal matrixwith on the diagonal the variances σ2

vi. Here i equals the number of PSs that is taken into account. It is

assumed that the deformation rates are uncorrelated, that is not the case because of atmospheric effects andunwrapping, see [53]. Normally these values are computed during the processing, however, they were notavailable yet.

5.7.2 External precision

The external precision describes the dispersion of the estimated unknown parameters. In this project, theestimated unknown parameters are the deformation rates of each PS. When inverse modeling is used to derivethe deformation parameters, dx and dz are the estimated unknown parameters, see also section 4.3 on inversemodeling.

The precision of the deformation rate (v) depends on the number and precision of the observations, but alsoon the temporal distribution of the observations. In fact the precision of the estimated deformation rate isthe same for all PSs. This is because of the fact that all PSs have observations in the same epochs, so the


5.8. FEASIBILITY 53

number and the temporal distribution of the observations are the same. Also the precision of the observations,described by the diagonal matrix Qyy, is the same. The precision of the deformation rate given by the varianceσ2

v , is calculated with the propagation law of the variances: Qxx = (AT Q−1yy A)−1, with A = (t1 ... tm)T .

For the precision of the deformation parameters computed with inverse modeling, see section 4.3 on inversemodeling.

5.7.3 Global Overall Model test

The internal reliability is a measure of the model error that can be detected with a certain probability. In otherwords: the internal reliability describes the performance of the statistical testing of the observations [48]. Inthis section, the Generalized Likelihood Ratio (GLR) test is used [48]. One possible model error is the errorthat the linear model is not valid. So, during the testing procedures, this alternative hypothesis Ha has to betested against the null hypothesis H0 that the linear model is correct. Here the Global Overall Model (GOM)test is used, this is a general test on discrepancies between the observations and the assumed model. Thismeans that the whole vector of observations is checked, but without having a specific error signature in mind.In this test, the number of independent errors (q) equals the number of observations (m) minus the numberof unknowns (n). This implies that there is no redundancy in the alternative hypothesis so the vector with theresiduals ea becomes zero. In that case, the test statistic T q = m − n can be written as:

T q=m−n = eT0 Q−1

yy e0 (5.3)

The test statistic T q=m−n is distributed as:

H0 : T q=m−n χ2(m − n, 0) , Ha : T q=m−n χ2(m − n, λnc) (5.4)

Where χ2 is the Chi-square distribution and λnc is the non-centrality parameter. The null hypothesis will berejected when:

T q=m−n > χ2

α(m − n, 0) (5.5)

Notice that only the GOM test is not sufficient to reject the null hypothesis. Rejection can be caused eitherby large (functional) errors in the observations (that are not covered by H0), an inappropriate model (H0) forthe data at hand, or by a poor specification of the observables noise characteristics in the stochastic model(through matrix Qyy), [48]. In the context of this project, it can be that the deformation is not linear at all, oronly for a certain period and not the whole time span. Also outliers in the observations can affect the OverallModel test.

5.8 Feasibility

The optimal product validation is a direct comparison with independent ground based methods such as leveling,tachymetry or GPS, these are the most widely used methods nowadays. The first thing to do, is the visualcomparison between the measurements, check if they show deformation at the same locations. Notice thatthe PSs are relative with respect to the reference point. So a possible uplift in the PS-InSAR measurements,while the validation dataset shows subsidence, can be due to a large subsidence of the reference point. Tocompare the magnitude of the deformation, the deformation in the radar line of sight has to be decomposedin the North, East and Up direction. Here inverse modeling can be used. After that, a scatterplot of bothdatasets can be made to visualize their correlation.



However direct comparison is not always possible, because of a lack of quantitative data. For this projectimages are used from the period 1992-2001, these are already 5 to 15 years old. From the start of themeasurements until now lots of things have changed; people left the company, organizations are reorganizedetc. However, it is possible to provide qualitative information such as the spatial limits of the deformationarea, an approximate assessment of the maximum deformation, the location of damage etc. These statementscan be verified by local experts. For sure this gives no hard numbers like they can be derived with validationdatasets.


Chapter 6

Case studies

6.1 Introduction

In this chapter describes the case studies that we performed, which are Harlingen, Kornwerderzand, Markenand Noordoostpolder. For each case study the methodology is described. This includes a description of thedeformation that the radar detects, the analysis of timeseries which follow from the persistent scatterers,estimation of deformation parameters and classification of the deformation. The methodology is followed bya section on quality assessment of the measurements and each case study concludes with an overview of theresults.

6.2 Case study Harlingen

In this section an overview is given on the results of the case study of Harlingen. Information on the history ofthe area and the used data can be found in appendix B. This section start with a description of the detecteddeformation. Finally the results and conclusions with respect to this case study are given.

6.2.1 Detection of deformation

If a histogram is made of the deformation rates in ascending track of the Harlingen area, this leads to figure 6.1.It can be seen that next to the main peak in the histogram, there is an additional smaller peak on the lefthand side. This is what is expected because of the fact that there is a subsidence bowl in the area, this will befurther explained in the following section. What also can be seen is that the mean of the histogram is about+ 5 mm/year of deformation. This is not very realistic, the hypothesis is that there is mostly subsidence andvery little uplift.

In the descending track (see figure 6.2), the subsidence bowl is not visible as a second peak, but more as ashallower slope on the left hand side of the main peak. Using the assumption that only very little uplift canoccur, the total data set can be shifted so that the main peak of the histogram now has very little, or no,deformation. The result of this shift is presented in the figures 6.3 and 6.4.

Clear is that the result is similar in both tracks. The area is generally quite stable, with exception of thepoints in the subsidence bowl. Especially in the ascending track, subsidence of up to 40 millimeters occurs.An overview of all data is presented in figure F.8.

55

56 CHAPTER 6. CASE STUDIES

Figure 6.1: Deformation rate in ascending track Figure 6.2: Deformation rate in descending track

Figure 6.3: Shifted deformation rate in ascendingtrack

Figure 6.4: Shifted deformation rate in descend-ing track

Triangles facing upwards are measurements in the ascending track, whereas triangles facing downwards aremeasurements taken in the descending track. A triangle with a large triangle around it is significant deforma-tion. This is deformation of more than 30 mm/year.

The yellow points are stable points, the dark blue points have a large deformation. There is a dark blue areain the middle of the figure, with some lighter blue points around it. Outside this area more yellow points canbe found. This is the subsidence bowl. It can be seen that there is a part of the dike that is also deforming.A comparison with the actual subsidence bowl is made in the next section.

Reference data

The subsidence near Harlingen is monitored by a permanent GPS station in the center of the subsidence bowl.Furthermore each year a leveling campaign is conducted. The estimated absolute subsidence due to salt miningfrom 1995 until 2005 in the area is shown in figure 6.5.

From figure 6.5 it can be seen that the primary dike along the coast has an estimated absolute subsidence of20 to 70 mm in 10 years. This leads to an approximation of the subsidence of 2 to 7 mm per year. This isrespectively 1.8 mm and 6.4 mm per year in the radar LOS.

The stretch of dike with more deformation than 60 millimeter a year is about 10 kilometers long, and liesapproximately 15 kilometers to the north of Harlingen. This is in correspondence with the area that subsides


6.2. CASE STUDY HARLINGEN 57

Figure 6.5: Estimated absolute subsidence due to salt mining [24]

with more than 5 millimeter a year in the radar image (Line of Sight deformation).

6.2.2 Quality assessment

The input parameters for the Overall Model test are a standard deviation the measurements of 6 mm. This is arelatively large number. The reason for this is probably the subsidence in the area, which leads to a coherencewhich is somewhat less than average. The significance level is set to 90%.

As can be seen in the figures F.9 and F.10, the ascending and descending track measurements are of similarquality. About the same percentage is accepted.

The plots on the standard deviation of the residuals from the linear model, figures F.11 and F.12, show thesame behavior as the overall model test figures. The magnitude of the standard deviation is comparable inascending and descending track.

The series of measurements of these points deliver an estimation of the subsidence rate in the area. Interestingto know is how accurate this estimation is. For the ascending track, the deformation rate is determined by aseries of 31 images. The descending track has a larger series of 74 images. The visible effect of this in theaccuracy of the estimation is that the descending track velocity is slightly more accurate than the ascendingtrack. Standard deviation of estimated velocity(mm) is for ascending track 0.47 mm/y and for descendingtrack 0.25 mm/y.

A striking thing to see is that the points in the subsidence bowl usually have a bigger standard deviation thanthe points on the edge of the bowl. This suggests that a linear model is not the best representation for thedata. This is interesting because the deformation due to salt mining should be linear [24]. The non linearityof the data can be explained with the time interval of the salt mining with respect to the time interval of theradar data. The radar data acquisition started 3 years earlier than the start of the mining, which started in1995. This causes a non-linear subsidence curve, and thus a larger standard deviation from the linear modelin the subsiding area. The effect is visualized in figure 6.6. Although the estimation is linear, the time seriesshow a sharp turn downwards around day -500.

Another explanation for the worse quality of the points in the subsidence bowl is that the processing methodsassume only a small deformation. In the subsidence bowl, the deformation is larger than the radar wavelength.This can lead to erroneous estimation.

The link between the Overall Model test figures and the standard deviation figures is clearly visible. Pointsthat are rejected in the Overall Model test, have a high standard deviation as well. This can be explainedby the following line of reasoning. A rejected point is usually rejected because of either a lot of noise in the



Figure 6.6: Example of time series in subsidence bowl

Segment ID Length(m) Orientationdike w.r.t.headingsatellite

anglebetween 0and 90degrees

#PSs #points / km

North 680 54 54 69 101Mid-north 1200 65.5 65.5 35 29Mid-south 1322 45.5 45.5 137 104South 2902 32.5 32.5 191 66

Table 6.1: The number of PSs for ascending orbit

observation, or a non linear deformation. In both cases, the standard deviation of the residuals from the linearmodel will be large. The overall model test will reject these points, because the linear model, which goes intothe test, does not fit properly. This leads to a big correlation between both datasets.

6.2.3 The number of Persistent Scatterers

The dikes of Friesland cause a lot of PSs, in the Harlingen case the dikes are somewhat comparable to thesituation in the Noordoostpolder (see section 6.5). To study the relation between the orientation of the dikeand the number of PSs the same method is used as in the case study of the Noordoostpolder. The dike isdivided in straight segments, as can be seen in figure 6.7. For all these straight parts, the orientation of thedike is calculated with respect to the heading direction of the satellite. From the center line of each part ofdike, an offset of 30 meter is applied to both sides of this line. This leads to a polygon that represents thatpart of the dike. After that, the number of PSs is counted for each part, the results can be found in table 6.1and table 6.2. Notice that the sidelobes are also counted. This number of sidelobes will be significant, butthe percentage of sidelobes is likely to be the same for all the different parts. This implies that these numbersmight only be used in a relative way.


6.3. CASE STUDY KORNWERDERZAND 59

Figure 6.7: Division of dikes in straight segments

Segment ID Length(m) Orientationdike w.r.t.headingsatellite

anglebetween 0and 90degrees

#PSs #points / km

North 680 207 27 4 6Mid-north 1200 218.5 38.5 5 4Mid-south 1322 198.5 18.5 4 3South 2902 185.5 5.5 134 46

Table 6.2: The number of PSs for descending orbit

It can be clearly seen that the amount of PS-points in the descending orbit is quite low in comparison to theascending orbit.

In figure 6.8 the relative dike angle is plotted against the number of points using a logarithmic scale. Arelation is not obvious; the hypothesis is that the number of PS-points decreases with an increasing angle(0-90 degrees). But due to the low amount of samples of dike segments this hypothesis can not be tested.This could be further researched by using more stretches of dike with more different orientations.

6.2.4 Summary of results

1. The dikes above Harlingen subside likely due to salt extraction

2. The detected subsidence of the dikes due to salt extraction is up to 6 millimeter a year for the area 10kilometers to the north of Harlingen. This corresponds with the estimated subsidence between 1995 and2005.

3. The subsidence due to the mining appears to be non linear, but this is mainly due to the time intervalof the radar acquisitions.

6.3 Case study Kornwerderzand

This section describes the results of the case study of Kornwerderzand. The research methodology anddescription of quality of the measurements are presented. Finally the results and conclusions with respect to



Figure 6.8: Relation between the number of points and the angle between the orientation of the dike andthe orbit of the satellite

this case study are given. Some background information on this location is presented in appendix C.


This section contains a number of steps. First, the method for identifying outliers is discussed. After this,some interesting locations are listed. A more detailed discussion of these locations concludes the section.

Estimation of deformation parameters and classification

In the final dataset there are a few points or areas that stick out. The locations of these points are: (seefigure F.13)

• The area near the bridges is interesting. The slope between the two roads which lead to the bridgessubsides on the eastern side, while the area on the western side of the bridge appears to experienceuplift.

• At the sluice, on the southern part of Kornwerderzand there are a number of interesting moving points.The area is quite sensitive to erroneous interpretation, because there are a number of possible outliersin it.

• The northern breakwater is also interesting. Descending points on this breakwater experience uplift inthe line of sight of the satellite.

The identified interesting locations will be discussed next seperately.

The bridge As can be seen in figure F.14, the points near the bridge show some interesting behaviour. Thebridge of Kornwerderzand consists of 2 independent halves. The bridges are movable in the horizontalplane. On the eastern side of the bridge a number of PSs are located. These scatterers are all in theascending track. They are located on a slope in the terrain, in between the two halves of the bridge. The


6.3. CASE STUDY KORNWERDERZAND 61

scatterers show a relatively large deformation rate, of more than 1 millimeter per year. On the westernside of the bridge are some scatterers as well. These scatterers are located on the house of the bridgekeeper, and on the walls just beneath the bridge. The most interesting about these points is that theyshow an inverse motion compared to the eastern side of the bridge; they experience uplift.

A visit of the area made clear that there are some signs of this deformation in the field as well. Thebridge structure shows a clear crack in the vertical wall on the northeastern side of the bridge. This canbe seen in figure F.15 and figure F.16. The photographs are taken from the northeast. These signs areexpected if the eastern side subsides, while the western side is stable or even shows uplift. The rupturethen occurs due to the characteristics of concrete: it can not handle pulling forces.

The sluice The area near the sluice is interesting, because a number of points show different motion, bothin ascending as in descending track. Extra caution is needed in this area, since the image is pollutedwith points that seem to be erroneous. More on the unreliable points is presented later in the sectionon quality description.

There are two points which experience a big uplift; these can be classified as outliers using the charac-teristics described in the beginning of the section. They are the dark red triangles in the central part offigure F.17. The house next to the sluice appears to subside, whereas the sluice itself has a number ofpoints which show minor uplift. The uplift is not significant, whereas the subsidence is.

This location was not investigated during the case study visit, since the area was not noticed as interestingyet at that stage. Data gathering in later stages did not provide any solutions for this problem.

The northern breakwater This area shows some strange deformation on the eastern half, measured by thesatellite when flying a descending orbit. The deformation is in the direction of the satellite, and couldbe interpreted as uplift or horizontal motion. The likelihood of such an event is not that high, since thedata on the other slope shows almost no deformation at all.


In this section some quality parameters are discussed, specified on the Kornwerderzand case. The first topicare some statistics on the area, after that a number of plots are presented illustrating the results of testingprocedures.

Statistics

The total length of dike-like bodies in the area of Kornwerderzand is 8207 meters. This total is a bit doubtful,since a large part of the area consists of breakwaters or plain island. The area of Kornwerderzand is 0.4276square kilometers.

There are in total 2487 points in the area of Kornwerderzand. It must be noted that a large part of this totalnumber of points are sidelobes. They are hard to separate from the main lobe. All sidelobes are used asobservation points. This is possible because we are interested in deformation only, and sidelobes do presentan accurate deformation rate.

Because the area of Kornwerderzand is not a real dike, the amount of points per stretching meter of dike isno meaningful statistic. The amount of points per square kilometer is a nice statistic however, it enables usto state something on the properties of the radar data. On the artificial island of Kornwerderzand the satellitemeasures 5816 points per square kilometer (measured in 2 tracks).

The series of measurements of these points deliver an estimation of the subsidence rate in the area. Interestingto know is how accurate this estimation is. For the ascending track, the deformation rate is determined by aseries of 58 images. The descending track has an even larger series, of 74 images. The effect of this on theprecision of the estimation is that the descending track velocity is slightly more accurate than the ascending



track. Standard deviation of estimated velocity(mm) is for ascending track 0.20 mm/y and for descendingtrack 0.17 mm/y.

Figures

In this section, some figures resulting from the testing scripts are presented. The first test that was performedis the Overall Model Test. This test describes to what extent the measurements behave according to our(linear)model. The input parameter for this step was a standard deviation of 4 mm, and a significance levelof 90%.

The main difference between both tracks appears to be the number of accepted points. The ascending trackmeasurements mostly behave according to our model, whereas the descending measurements appear to beworse (which is due to a longer time interval of the measurements). The coherence is directly dependenton the standard deviation of the individual measurement residuals with respect to the linear model. This isplotted in the figures F.21 and F.22.

From figure F.21 and figure F.22 we can deduce that the model of the descending points fits worse than themodel of the ascending points. This can be a reason for the rejection of the points in the overall model test.This is pointed out more clearly in figure F.23, where the points that are rejected in the overall model test aremade black.

If we now make a plot of all points that are not rejected by the overall model test, we get figure F.24. Onecould defend that the points which are rejected by the overall model test, show no clear linear deformation(with acceptable noise level) and are thus not usable in interpretation of the data. With this statement, wecan argue that figure F.24 is the only usable figure to use for interpretation.

The points with the big triangle around it are now points with more or less reliable, significant deformation.If this point is not isolated, something is bound to be happening at this location. Clearly visible in figure F.24is that there are almost no points with reliable significant deformation, and most points which do answer tothis criterion are isolated. Therefore, we can state that the area is generally stable. The only things that moveare buildings and other structures, like bridges. These kinds of deformation can be categorized as autonomousmovements.

A lot of the points which behaved in a strange way on the northern breakwater, which was first consideredas an interesting location, are rejected in the overall model test and are thus not visualized in figure F.24.However, the other 2 locations are still in the picture. The subsiding points at the bridge survived the overallmodel test, and some subsiding points near the sluice did as well. Most points at the sluice vanished however.


1. The artificial island of Kornwerderzand is generally stable.

2. There are a number of autonomous movements going on at the structures on the island. These pointsare not local deformation, because they are measured on structures.

3. The bridge appears to subside on the eastern side, the reaction of that is a slight uplift of the samebridge on the western side.

6.4 Case study Marken

The dikes of the island Marken are a part of the primary dikes of the Netherlands. It is a special part, becausethe island is of a high importance in both cultural and historical point of view. The area of Marken has been


6.4. CASE STUDY MARKEN 63

chosen as a case study not only because of the availability of locations with deformation in the PS-InSARdatasets for these dikes, but also because of the prior knowledge of the dikes’ status. A short investigationmade clear that a part of the southern part of the ringdike (at the location of the numbers 13 to 15 in figureF.26) is known to be in a bad maintenance state. The responsible agency for the dikes is RWS, departmentNoord-Holland. Information about the history of Marken, the dikes and the used datasets can be found inappendix D.


As was visualized in figure F.25 there are many PS-InSAR points in the ascending and descending image ofMarken on the Markerwaard dikes, but less points on the ring dike. A short inspection of the PS-InSARdata of the Markerwaard dikes showed that these dikes are stable. They almost all have a deformation lessthen 1 mm/year in the radar LOS and are therefore spatially correlated. Ascending and descending scatterersshow the same deformation rates as well. Most of the points on the Markerwaard dikes have sidelobes, whichindicates that these points can not be classified as noise. Therefore the PS-InSAR points on the Markerwaarddikes are considered as stable points. On both Markerwaard dikes, the Bukdijk as well as the Kruisbaakdijk,one location was chosen as an representative location. At exactly this location both ascending and descendingPS-points are available and the time series of those points were analyzed.

For the ring dike the situation is totally different. Only on the western part of the ring dike, near theKruisbaakdijk, there is a high number of spatially correlated PS-InSAR points, but this holds only for theascending dataset. Most other points in both ascending and descending dataset are isolated. Also a lot ofthese points did not have any sidelobes. In total there are 28 scatterers at the entire ring dike. Three ofthese points have a very low coherence and are therefore classified as an outlier. All the other 25 points(ascending and descending) show deformation rates of about 5 to 15 mm per year. For this reason they arespatial correlated and can be classified as deformation. The position of the PSs are visualized in figure F.26.

6.4.2 Time series analysis

The time series of each of the interesting locations were computed. The time series of some representativelocations can be seen in figure 6.9. The corresponding estimated deformation velocity in the LOS, the estimatedtopographic height and the coherence are also given in these figures. All time series of the PS-InSAR pointsat the ring dike show the same trend of deformation over the entire time span: around 5 to 15 mm per year.The Bukdijk and Kruisbaakdijk show a deformation of 0.5 to 1 mm per year. It is also clearly visible that thereare some deviations of this estimated linear deformation, which can be recognized in all time series of theinteresting locations. In the time series of the locations on the ring dike these deviations appear to be periodicor even seasonal, see figure 6.9. Therefore the water level measurements of the Markermeer were consulted,because they might give information about the tidal effects, which could indicate changes in external pressureon the dike. The water levels did not change much in the acquisition period of the radar data.

6.4.3 Estimation of deformation parameters

To be able to determine the mechanism that causes the deformation that is visible in the PS-InSAR datasets,an overview of all estimated deformation velocities at the identified locations is given in figure F.41. For properestimation of the horizontal and vertical components of deformation, data in ascending and descending trackis needed. The deformation in vertical direction is preferred, because this deformation is expected to be thelargest. The northern part of the ring dike is rebuilt in the period of the measurements, so some settlement,which has mainly a component in the vertical direction, is expected. To study a possible subsidence of thewhole island, also some points in the village of Marken were considered.

An overview of the estimated vertical deformation velocities and their variance can be seen in table 6.3. These



Figure 6.9: Time series for some characteristic locations

values are calculated according to the method described in section 4.3. The values are grouped into the areasof the Bukdijk, Kruisbaakdijk, ring dike and the village of Marken.

6.4.4 Classification

The assumption is made that the radar only reflects at one side of the dike, the outer side, because at thisside there is a stone layer. The exact location of the scattering object is not known. There are hardlyany ascending and descending PSs available at the same location. This causes difficulties when decidingabout the deformation mechanism that caused the measured deformation. One deformation mechanism iseasily explained, since it is known that the northern dike is reinforced in 1994. Therefore, the deformationmechanisms settlement is assumed to cause the deformation.

dz ascending σ2

dzascending dz descending σ2

dzdescending

Village Marken -2.5 0.09 -2.0 0.17Ring dike Marken -6.4 0.20 -9.9 0.82Bukdijk Marken -0.6 0.06 -0.3 0.21KruisbaakdijkMarken

-1.2 2.09 1.0 0.37

Total of Marken -2.1 0.03 -2.4 0.06

Table 6.3: Estimated vertical deformation velocities (mm/y) and their variance.


6.4. CASE STUDY MARKEN 65

From table 6.3 can be seen that the magnitude of the estimated deformation velocity in the village of Markendiffers from the estimated deformation velocity of the ring dike. Therefore it is safe to state that the measureddeformation on the ring dike can not be caused by just subsidence of the whole island. However, it is very wellpossible that the island of Marken is subsiding a bit due to compaction of a the peat layer below the entireisland. The geotechnical profiles show that there is a peat layer below the entire ring dike at a depth of 5meter. The ring dike shows a larger deformation rate than the village. The southern part of the ring dike isolder and weaker than the northern part. Because of a lack of PS-InSAR points at the southern part of thedike, no assumption on the deformation mechanism can be made yet.

The Bukdijk and Kruisbaakdijk are quite stable, which can be explained by the fact that they were built on astable layer, about 50 years ago. Before the dikes were built, a so called ”cunet” was dug. This means thatthe weak peat layers where dredged away and were replaced by a layer of sand.


The precision of the estimated deformation parameter is described with use of the standard deviation ofestimated velocity. This precision was 0.31 mm/year for the ascending track and 0.35 mm/year for thedescending track. To be able to describe the reliability of the assumed linear deformation model, the GlobalOverall Model (GOM) test was conducted. The results of the applied overall model test with a power of 90%and a standard deviation of 6 mm can be seen in figure F.27 and figure F.28. Normally, for corner reflectorsa standard deviation of 2 mm is used. The big difference is due to the fact that corner reflectors are idealscatterers; the natural scatterers give worse reflections. The large amount of rejected PS-InSAR points canbe clarified with a closer look on the standard deviation of the residuals from the linear deformation model foreach PS-InSAR point (see figure F.29 and F.30). This picture shows that the standard deviations of almostall PS-InSAR points are in the interval of 5 to 10 mm. The points that are accepted have a high coherencevalue and are also the points with a high number of sidelobes. The isolated PSs are not accepted, this is mostlikely due to the big standard deviation of the residuals. Other reasons can be that the used linear model isnot valid or the atmospheric estimation can be improved.

One of the used datasets is the leveling and GPS measurements from RWS (see [46]). The leveling dataand the GPS measurements can be used to validate the PS-InSAR measurements. Of the ring dike there isleveling data available from 1996, 1997, 1998 and 2001. The locations of these measurements can be seen infigure F.31. The leveling was conducted using steel tubes in a concrete shell (numbers in red) and yellow spotspainted at the path on the crest of the dike. The measurements are with respect to NAP and connected withlevel marks (numbers in orange). Some GPS measurements were performed with the use of four referencepoints (numbers in green) to get information on the horizontal movement of the dikes.

For the validation of the radar data, the leveling data of the steel tubes between 1996 and 2001 was used.The results of the leveling measurements can be seen in figure F.32. The yellow marks on the path were onlyused as intermediate locations and were not considered to be stable in the time span of the measurements.The GPS measurements (see figure F.33) made clear that the vertical deformation is larger than the horizontaldeformation.

The total deformation between 1996 and 2001, measured with leveling, is recalculated into a deformation rateper year (see the column ’leveling deformation/yr’ in table 6.4). For each steel tube, all PS-InSAR pointsin the surrounding of the corresponding tube where selected. Of these PS-InSAR points the mean verticalcomponent of the estimated deformation velocity was calculated, which can be found in column ’mean radardeformation/yr’ in table 6.4. The differences between the radar and leveling deformation rate can be found inthe column ’difference’.

It must be taken into account that the leveling data do have a known reference, namely the used benchmark atthe top of the dike, whereas the location of the PS-InSAR measurements is not known exactly. It is assumedthat the radar reflects at the wave breaking stones. This means that the deformation rates of the leveling andPS-InSAR are not necessarily the same.



Tube # PS-InSAR#

meanradardeforma-tion/yr

levelingdeforma-tion/yr

Difference Differencebetweentwopoints(radar)

Differencebetweentwopoints(leveling)

Doubledifferenceradar andleveling

9 1-5 -3,6 -4,4 0,812 6-12 -5,7 -5,2 -0,5 2,2 0,8 1,423 14-15 -13,3 -10,8 -2,5 7,6 5,6 2,049 26-27 -15,1 -10,8 -4,3 1,8 0,0 1,855 25 -7,3 -8,8 1,5 -7,8 -2,0 -5,861 23 -13,5 -12,8 -0,7 6,2 4,0 2,264 19-22 -14,7 -11,6 -3,1 1,2 -1,2 2,470 17-18 -14,8 -9,8 -5,0 0,2 -1,8 2,073 16 -17,3 -12,4 -4,9 2,5 2,6 -0,1

Table 6.4: Overview radar and leveling measurements (mm).

Figure 6.10: Scatter plot of the PS-InSAR and leveling measurements

In order to be able to provide a more reliable comparison between the leveling and PS-InSAR data, the doubledifferences between the PS-InSAR and leveling measurements are calculated. The differences in deformationrate between two following leveling tubes are calculated for both PS-InSAR and leveling data, see columns’Difference between two points (PS-InSAR)’ and ’Difference between two points (leveling)’. The final doubledifferences can be found in column ’Double difference PS-InSAR / leveling’. To give a better insight in therelation between the PS-InSAR and leveling results a scatter plot was made, see figure 6.10. This scatter plotmakes clear that there is correlation between the radar and leveling data.


• The Bukdijk is completely covered with grass and small trees. Most PS-InSAR points can be found onthis dike. For this reason it is assumed that the radar signal is reflecting on the wave breaking stones atthe water side, because normally vegetation suffers from temporal decorrelation. It is assumed that thisis the case for the ring dike of Marken as well.

• There are more PSs at the Bukdijk than at the ring dike. This can be explained by the fact that the ringdike is maintained every 5 years while the Bukdijk is not maintained at all. The wave breaking stonesat the ring dike are replaced after several years, this will lead to temporal decorrelation. This makes


6.5. CASE STUDY NOORDOOSTPOLDER 67

it unlikely that the ring dike can be monitored with PS-InSAR over longer periods than 5 to 10 years.Nipping ice disturbs the wave breaking stones as well. This makes it impossible to detect deformationdue to nipping ice.

• To be able to describe the reliability of the assumed linear deformation model, the Global Overall Model(GOM) test was conducted. The points that are accepted have a high coherence value and are also thepoints with a high number of sidelobes. The isolated PSs are not accepted, this is most likely due tothe big standard deviation of the residuals.

• Both PS-InSAR and leveling data show a deformation in the vertical direction of about 10 mm peryear at the ring dike. The deformation measured with PS-InSAR appears to be a bit larger than theleveling data. This can be explained by the fact that not the same objects are measured. But becausethe magnitude is almost the same, it is likely that the measured deformation mechanism is the same.This mechanism is probably compaction of the peat layer below the dike due to the weight of the dikeitself. On the northern part of the ring dike there is probably settlement as well, because this part wasreinforced in 1994.

• The southern part of the ring dike showed the same magnitude of vertical deformation as the northernpart of the ring dike in both PS-InSAR and leveling data. But the GPS data showed also horizontaldeformation perpendicular to the length axis of the dike near the locations of some PS-InSAR measure-ments. According to the civil inspector of Marken this is probably due to a combination of nipping iceand high water. But as mentioned before, nipping ice will disturb the stone layer. This leads to a lossof PSs and makes it not possible to observe the horizontal deformation with PS-InSAR.

• The Bukdijk and Kruisbaakdijk appear to be quite stable. A drawback is that there is no leveling dataavailable of these dikes to verify this statement. The PS-InSAR points in the village of Marken are notcompletely stable, the mean trend is a small subsidence. This is probably due to compaction of the peatlayer below the entire island.

• The conclusions that can be drawn based on the PS-InSAR measurements about the magnitude of thevertical deformation are in correspondence with the measurements of RWS (see [46]). They concludedthat a monotonous deformation of 10 to 15 mm per year appeared at the ring dike. But to determinethe horizontal deformation mechanism from the PS-InSAR measurements only, more PS-InSAR pointsin both ascending and descending dataset are needed, so the LOS deformation can be decomposed in ahorizontal and vertical component.

6.5 Case study Noordoostpolder

The Noordoostpolder is a part of the so called Zuiderzee Works. The Zuiderzee Works are a man-made systemof dams, land reclamation and water drainage works, and they are the largest hydraulic engineering projectundertaken by the Netherlands during the twentieth century. The project involved the damming off of theZuiderzee, a large, shallow inlet of the North Sea, and the reclamation of land in the newly enclosed waterbody by means of polders. Its main purpose was to improve flood protection and create additional land foragriculture. In the following section the case study of the Noordoostpolder is described. It contains the resultsand conclusions of this particular case study. A more extent background information of this case study can befound in E.


Based on the methodology, explained in section 5.5, all PSs points that are on the dike or around it were ana-lyzed and classified to outliers, autonomous movement (or local deformation), stable point, and deformation.Figure F.34 shows only the PSs that are located on the dike with the results of the detection step. Based onthese results, the dike is classified in three areas and three detected deformation areas were chosen for furtheranalysis (Case A, B, and C in figure F.34):



The areas which were classified as autonomous movement contain some isolated PSs (spatially uncorrelated)that show a deformation signal. It is also possible that these points show local deformation mechanisms, i.e.deformation in a small part of the dike. These areas are visualized in figure F.34 by the orange color thatshows that this area needs more investigation.

6.5.2 Time series analysis

For all PSs in case A, B, and C time series analysis was performed to check the validity of linear model and tostudy other possibilities for phase unwrapping. We visually checked, for all PSs in the detected deformationareas, the possibilities for phase unwrapping and did not see any other solution for the phase unwrapping.The results of this step for the validation of the linear model are presented for each location (A, B, and C)separately.

• Case A: Most of the PSs in this area show a deformation signal in the LOS direction of about 1.6 to3 mm/year. Also, both ascending and descending observations show approximately the same signal.Figure 6.11 shows some examples of the time series in this area. As it can be seen, the linear modelis not feasible for the entire time period. It is more likely to have a linear or exponential trend in thefirst half of the time period, after that, the deformation becomes stable, see the alternative models infigure 6.12.

Figure 6.11: Some time series for Case A.

• Case B: This part of the dike, show two kinds of PSs that show a different deformation signal. ThesePSs are divided in two groups: B1 and B2. Figure F.35 shows the location of these two kinds of PSs.

Figure 6.13a and figure 6.13b show the time series of one PS in the B1 part for both ascending anddescending orbit. These time series are similar to the deformation signal of Case A. The PSs in theB2 segment show a linear deformation over the whole period analyzed radar data, see figure 6.13c



Figure 6.12: Alternative time series for Case A.

and figure 6.13d. Also, this second group of PSs shows the considerable difference in ascending anddescending observations. Comparison of the locations of these two groups of points reveals that theyare also spatially separated. So, we concluded that case B can be split up into two parts with differentdeformation mechanisms.

• Case C: The observations in this segment are spatially variable. We detected two different groups ofPSs. The first group shows the stable behavior during the whole time period (figure 6.14a) and thesecond group shows approximately linear deformation signal (figure 6.14b).

6.5.3 Estimation of deformation parameters

Using the approach explained in section 4.3, the detected deformation in the areas A, B, and C were decomposedto the dx and dz. In this section, the results are summarized:

• Case A: Because of the availability of both ascending and descending observations in this segment, itis possible to decompose the detected deformation to the dx and dz. However, as both observationsshow the same signal (average of 1.7 mm/year), with the same temporal behavior, it is also likely thatthe horizontal deformation is not significant. So, we derived deformation parameters for both situations.The estimated deformation parameters (using decomposition) is dx = - 0.9 mm/year and dz = -1.5mm/year. With the assumption that dx=0, the deformation in up direction, derived as: dz , becomes-1.95 mm/year.

• Case B: We derived the deformation parameters for the cases B1 and B2 separately. As, ascending anddescending observations show the same signal in the B1 case, we derived the deformation parametersfor this case also with the assumption of no horizontal deformation. For B1, dx = -1.7 mm/year anddz = 1.38 mm/year. With the assumption of no horizontal deformation, dz was estimated as dz = 1.8mm/year. For B2, dx = -2.1 mm/year and dz = -2.9 mm/year.

• Case C: As only ascending observations are available in this part of the dike, it is not possible to deriveboth deformation parameters. Therefore, with the assumption of dx=0, the estimated deformation inup direction for this segment is dz= -1.42 mm/year. We used only the PSs which had been defined asdeformation in the detection step.



Figure 6.13: Some time series for Case B.

6.5.4 Classification

Based on the results of the last step and additional information about the dike, the detected deformation areas(A, B, and C) are classified to different deformation mechanisms. The methodology of this classification hasbeen described in section 5.6.

• Case A: Due to the similarity between both ascending and descending observations, it is assumedthat there is no horizontal deformation in this area. With this assumption, we classified the detecteddeformation as settlement.

Besides, we tried to support this result with some additional information and ground truth. Accordingto some engineering drawing(see appendix E), parts of this dike have been improved in 1992; a newsheet piling has been placed in combination with a new layer of rubbles (figure E.4). This was the casefor a part of the area of detected deformation. Actually, we have also deformation at the east-westpart of the dike. However, as it is mentioned before, parts of the details of these improvements arelost. This is the case for that east-west part. Something happened, but it is not known what, [Mr. J.Boezeman, waterboard Zuiderzeeland, oral communication, 30 October 2006]. The weight of this newlayer was about three thousand kilogram per meter. This additional weight results in a compaction ofthe soil layers under the dike. As there is the clay layer under this part of the dike, this compactionbecomes more feasible and it is possible to be observed with our technique as settlement. Due to the factthat settlement has an exponential behavior in time, which is also visible in the time series of this area(figure 6.12), the results are comparable with the expectations. So we can conclude that we measureddeformation is due to this new stone layer in this dike segment.

• Case B: We analyzed the cases B1 and B2 separately. The deformation signals in the B1 case showmore or less the similar behavior as the deformation of case A. Also the results of our method classifiedthis area as settlement. Similarly, this part of the dike has been improved in 1992, also with a new stonelayer. So, we expect the same cause of deformation for these two parts of the dike.



Figure 6.14: Some time series for Case C.

σdx (mm/year) σdz (mm/year) dx= 0, σdz (mm/year)Case A 0.37 0.04 0.36Case B1 0.10 0.04 0.25Case B2 0.10 0.04 Not relevantCase C Not relevant Not relevant 0.09

Table 6.5: The external precision of the estimated deformation parameters

For the case B2, our method classified this part of the dike as deformation due to an imminent slidingof the outer slope or a sliding of the protective cover. For this part we have no additional information.However, it is known that in the Noordoostpolder the protective cover tended to slide away. It might bethat that the measured deformation is due to this kind of sliding.

• Case C: In this segment, half of the PSs are stable and the remaining half show a deformation signal.Because of this spatial variability and noisy character of the observations, it is difficult to assign specificdeformation mechanism to this segment. As only ascending observations are available, so it is assumedthat there is no horizontal deformation, we classified this deformation as settlement.

However, the deformation classification and interpretation in this segment becomes very tricky due to thenoisy observations, small magnitude of the deformation(0.6-1.4 mm/year), lack of additional deformationand ground truth , and the availability of only ascending observations.


In this paragraph it is explained how to decide about the feasibility of the results and conclusions based onthe PS-InSAR data.

The external precision

In this section the external precision of the estimated deformation parameters is presented. The results aresummarized in table 6.5.

As can be seen in table 6.5 the external precision is quite high. It should be noticed that these numbersrepresent an ideal situation. The number of unknowns is maximal two while the number of observationsequals hundreds of points. Also it is clear that the precision of dx depends on the orientation of the dike, like



it is explained in section 4.3. The orientation of the dike in case B1 and B2 is almost vertical, which implies agood precision. The orientation of the dike in case A is partly vertical and partly not. This will decrease theprecision of the estimated deformation in the horizontal direction.

Overall Model Test

To derive the quality of our final results, we performed Overall Model Test(see section quality) for all detectedPSs on the dike. The results of this test are presented in figure F.36.

As you can see in this figure, most of the points that show a deformation signal are rejected in the OverallModel Test. The rejection of the test can be related to different issues, see section 5.7. However in our case,we see the high dependency between the rejection of the test and the detected deformation. The main reasonfor that could be the invalidity of the linear model for the detected deformation mechanisms. There are alsosome PSs which show a large deformation signal (2 to 4 mm/year) and are accepted in the test, especially inthe case B2. As we discussed before, most of the PSs in this part show a linear behavior over the whole timespan. But, most of the points which show a deformation signal in the cases A, B1, and C were rejected inthe test. This is in agreement with our expectation for these areas, as most of the PSs in these parts do notshow a linear behavior over the whole time span. So we can conclude that the linearity of the model for thetime interval of the analyzed radar data is not a realistic assumption for the dike deformation mechanisms asdetected in this area.

Validation

Like it is stated before, there are no validation datasets available for this case study. This means that thevalidity of the conclusions cannot be proven. However, especially in the case of settlement there are modelsthat can be used to calculate the expected magnitude of settlement. The formula of Koppejan [45] is awell known formula. For this formula, some constants have to be specified, like the primary and secondarycompression constants. These constants are dependent on the soil type and characteristics of the compressedlayer. Notice that the settlement is divided into an primary part and a secondary part. The first part is moreor less the short scale settlement, the secondary part the long scale settlement. The primary part ended whenthe deformation become a straight line. Also the old grain pressure has to be calculated, which equals tothe ground pressure minus the water pressure. The new grain pressure equals the old grain pressure plus thenew load. The last parameter is the level of consolidation (consolidatiegraad) which depends on some groundcharacteristics. The fact that there is a clay layer below the protective cover on this dike explains why theprimary settlement takes a while. Clay let, in opposite to sand, water badly through it. Another importantpoint is that the clay which can be found on those dikes is known as tough clay. This causes high valuesfor the primary and secondary compression constants, which implies a smaller expected deformation. For thisproject, the expected settlement is not calculated. However, in our case we are on a dike that has already aprotective cover for more than fifty years in 1992. This protective cover causes settlement of the dike in thepast. As a consequence a new load will not give the same magnitude of settlement as in the case without aprotective cover. To take this effect into account, more advanced models have to be used.

6.5.6 The number of Persistent Scatterers

It was already mentioned that the IJsselmeer dikes of the Noordoostpolder have a lot of PSs. In this section,the number of PSs is researched. To study the relation between the orientation of the dike and the numberof PSs, the dike is divided in straight segments, see figure 6.15, so the curved parts of the dike are not takeninto account. For all the straight parts, the orientation of the dike is calculated with respect to the headingdirection of the satellite. From the centerline of each part of dike, an offset of 30 meter was applied to bothsides of the line. This polygon represents the total area for that part of dike. After that, the number of PSsis counted for each part. The results can be found in table 6.6 and table 6.7. Notice that the sidelobes are



Figure 6.15: Division of dikes in straight segments.

also counted. This number of sidelobes will be significant, but the percentage of sidelobes is likely to be thesame for all the different parts. This implies that these numbers might only be used in a relative way.

In figure 6.16 the number of points per kilometer is plotted against the angle between the orientation of thedike and the orbit of the satellite. For ascending orbit, there is a clear relation between the angle and thenumber of points. The larger this angle, the smaller the number of points. For the first two points, thedifference in angle is not really significant, (just 4 degrees). So for the South dike part2, local differences atthe dike or the number of sidelobes might cause the larger number of points per kilometer. For descendingorbit this trend is less visible, however, the numbers of points for the different parts is also much smaller,notice the logarithmic scale of the y-axis. This can be expected for those parts where the orientation of thedike is almost parallel to the orbit of the satellite. With a right looking radar the ascending satellite is lookingto the outer side of the dike, while the descending satellite looks to the inner side of the dike. While the innerside of the dike is fully covered by grass, the outer side has some protective cover, which likely causes thesegood reflections. For these parts that are more or less perpendicular oriented with respect to the orbit, thedifferences are more difficult to explain. Probably local differences play a role here. The relation between the

Segment ID Length (m) Orientationdike w.r.t.heading sat.(346◦)

Angle between0◦ and 90◦

#PSs #Points / km

South dike part1 5450 104 76 200 37South dike part2 4520 161 19 2012 445South dike part3 1060 138,5 41,5 178 168North dike part1 10640 15 15 2608 245North dike part2 8180 46 46 720 88North dike part3 2410 97 83 32 13

Table 6.6: The number of PSs for ascending orbit



Segment ID Length (m) Orientationdike w.r.t.heading sat.(346◦)

Angle between0◦ and 90◦

#PSs #Points / km

South dike part1 5450 260 80 43 8South dike part2 4520 317 43 44 10South dike part3 1060 294,5 65,5 9 8North dike part1 10640 171 9 192 18North dike part2 8180 202 22 62 8North dike part3 2410 253 73 41 17

Table 6.7: The number of PSs for descending orbit

Figure 6.16: Relation between the number of points and the angle between the orientation of the dike andthe orbit of the satellite.

number of PSs and the coverage of the dike is also clearly visible in another part of the same dataset. At thenorth-west of Lemmer, there is a peat dike, fully covered by grass, here no PSs are found.


During this case study, we first tried to detect deformation of the Noordoostpolder dike and in a second stepwe tried to classify and interpret the detected deformation. The first step resulted in some interesting partsof the dike that show deformation. Two of the interesting parts are classified as settlement. For both parts,we conclude that this settlement is due to improvement works in 1992. In this year, a new stone layer wasplaced on the outer side of the dike. One part is classified as sliding of the protective cover, which is notunlikely because of experiences in the past. One part is not classified, because of the noisy character and thespatial variability of the measurements. The obvious point is that we can detect deformation of this dike inthe level of mm deformation per year. However, classification, interpretation, and finding the reasons of thedetected deformation is not a straightforward task and need more additional information about the dike andmore advanced technical knowledge about the deformation mechanisms. Also, the quality assessment of theused method for detection and classification needs more ground truth information which is not available forall deformation areas.


Chapter 7

Conclusions and recommendations

In this chapter the answers are presented at the research questions posed in the introduction. This chapterstarts with the answer on the main research question, followed by the answers of the subquestions. Thechapter ends with an overview of the recommendations for further research.

7.1 Answer on main research question

In this section the answeron the main research question will be discussed. The main research question asstated in the introduction was:

Is the PS-InSAR technique feasible for dike (deformation) monitoring in the Netherlands from a technical pointof view?

In short the answer is yes, the technique is feasible. During this project, deformation of dikes were detectedand classified for some case studies. In almost all cases, a reasonable interpretation was found. The validationdatasets, available for some case studies, show comparable results. This technique is especially usable todetect locations on the dikes which need more investigation. However, the interpretation of the PS-InSARresults is not straightforward and needs a strong collaboration of radar and dike experts.

7.2 Conclusions

In this section the conclusions are presented for all the subquestions as defined in the introduction. Eachconclusion is followed by a short discussion, where the main line of reasoning is given.

7.2.1 Characteristics of dikes

Research question 1: What are the important characteristics of dikes with respect to PS-InSAR?

The amount of PSs on the dikes depends on the kind of protective cover. Most dikes have a collar mattress(kraagstuk) covered with rubbles on the boundary of water and land. These rubbles acts like natural cornerreflectors and cause a lot of PSs. The orientation of the dike does not have a significant influence on thenumber of points per kilometer.

This technique does not work for dikes which are fully covered by grass: This can be seen in the dataset

75

76 CHAPTER 7. CONCLUSIONS AND RECOMMENDATIONS

of Noordoostpolder where all dikes contain a lot of PSs, except the peat dike near Lemmer, which is fullycovered by grass. Only objects on such dikes might cause a reflection. In fact this is expected, vegetationis temporally uncorrelated, which implies a low coherence, and thus no PSs. To increase the applicability invegetated areas, corner reflectors could be placed on dikes which are fully covered by grass. However, furtherresearch is needed to study the feasibility and effectiveness of this solution.

7.2.2 Detection and identification

Research question 2: Which types of deformation can be detected and which deformation mecha-nisms can be identified?

The deformation due to the following nine deformation mechanisms can potentially be detected with PS-InSAR:

• Deformation due to a precursor sliding

• Deformation due to a precursor sliding of the inner slope

• Deformation due to a precursor sliding of the outer slope

• Deformation due to seepage

• Deformation due to sliding of the protective cover

• Horizontal deformation of a dike

• Settlement

• Subsidence

• Swelling

Different issues affect the deformation detection. The first is the temporal behavior of the deformationmechanism. The probability of detection is small when it occurs in a short time period with respect to therevisit period of the satellite. Some deformation mechanisms are not detectible at all, since they take placebelow the water level. Another factor may be the magnitude of the deformation with respect to the radarwavelength. A large, near-instantaneous deformation might cause an unwrapping error. This means that inthe areas with a deformation rate larger than the wavelength between two radar acquisitions, the estimateddeformation become inaccurate. This means that large deformation components cannot be measured properlywith this technique. The detected deformation can be classified to these nine deformation mechanisms.Although every deformation might potentially be detected with radar, the probability of correct classificationincreases for strong spatially correlated phenomena. This probability depends on the number of PSs and onwhether the deformation can be detected on both sides of the dike or just one side.

Correct classification of small local deformation without spatial correlation is not likely. Anomalous points,surrounded by other points, that show spatially uncorrelated deformation, frequently need further investigation.There are three possibilities for the interpretation of such points: noise, autonomous movements or localdeformation. In the first two cases, the dike does not deform. Interpretation of these PSs usually requiresfield observations and further investigation about the scattering object and the dike itself. In those cases, thePS-InSAR data might be used to indicate whether further research is necessary.


Research question 3: What is the quality of the results of the PS-InSAR technique in dike monitoring?


7.2. CONCLUSIONS 77

According to the heading of the satellites (north-south), the radar is most sensitive to vertical deformation,reasonably sensitive to east-west deformation and not very sensitive to north-south deformation. For a dikewith an orientation perpendicular to the heading direction of the satellite, only the deformation in the z-direction can be measured. The consequence of this is that not all possible deformation components can bemeasured and the interpretation may become difficult. We can assume that a deformation along the lengthaxis of a dike is not likely. New satellite missions in the future with other orbital configurations may solve thisproblem.

The precision of the derived deformation rates and components is in the order of sub millimeters.

The quality of the estimated deformation rates and components depends on different factors, such as spatialdistributions of the PSs, land cover, rate of motion and linearity of deformation. An important issue is theassumption about the linearity of the deformation. In the current processing steps, it is assumed that thedeformation is linear over the full measurement period. However, the assumption of linearity is related to thetime interval of the analyzed radar data with respect to the temporal behavior of the deformation mechanism,i.e. the assumption for a particular deformation mechanism might be only valid on a short time interval. Thereare several possibilities where the assumption of linearity over the full measurement period is not correct:

1. There is deformation over the full measurement period, however the deformation is not constant overtime (a clear example is settlement).

2. The deformation is linear, but does not cover the full measurement period, just a part.

3. The deformation is not linear, and does not cover the full measurement period. These are the elasticmovements.

4. The superposition of different deformation mechanisms can cause a non-linear behavior in time. Thiscan be due to the fact that different deformation mechanisms have different temporal behavior.

All of these factors and also opportunistic nature of the technique require expert interpretation, i.e. collabo-ration of radar experts and dike experts.

Interpretation of the measurements on dikes is optimal when:

1. Both ascending and descending measurements are available. In this case it may be possible to derivethe full deformation vector, assuming that the deformation along the length axis of a dike equals zero.When only ascending or descending measurements are available, only for spatially correlated phenomenaon a curved dike an indication about the directions of the deformation can be derived. Deformationperpendicular to the length axis of the dike implies that the magnitude of the deformation is not thesame over the whole, curved dike.

2. There is a single deformation mechanism. A possible superposition of deformation mechanisms mayharm the spatial correlation of a certain deformation mechanism.

3. PSs are found on both sides of the dike. Some deformation mechanisms influence both sides of thedike, see section 2.2. PSs on both sides help in the evaluation of the different possibilities for thesemechanisms.

7.2.4 PS-InSAR with respect to the needs

Research question 4: To what extent does PS-InSAR fulfill the needs for dike deformation monitoringin the Netherlands?

According to the ”Voorschrift Toetsen op Veiligheid”, the dikes in the Netherlands should be monitored everyfive years. Based on its large spatial coverage and its short revisit period (monthly), PS-InSAR technique can


78 CHAPTER 7. CONCLUSIONS AND RECOMMENDATIONS

effectively be applied as an indicator method to continuously monitor the dikes of extended areas to detectlocations which needs a more detailed investigation. However, this technique cannot be used for dikes thatare fully covered by vegetation.

Also the opportunistic nature of this technique makes the successful application of this method dependentspecific condition, such as the number and location of the PSs.

Furthermore this technique can contribute to the scientific researches about dike deformation monitoring.Until now, no measurements of dike deformation are available with millimeter precision, which have the samespatial and temporal coverage. Since general knowledge on the behavior of a dike at millimeter level is limited,PS-InSAR can be used to provide new insights in the behavior of a dike at those scales.

7.3 Recommendations for further research

In this section, some recommendations for further research are given. These recommendations were collectedmainly from the conclusions, but also from the rest of this report, where justification may be found. The listis certainly not exhaustive, but only provides some suggestions to make a next step in this research.

1. The present research focused on the technical feasibility. To make the technique operational for practicaluse the economical feasibility should be studied next.

2. Study the integration of this technique with other measurement techniques to fulfill all the demands fordike deformation monitoring.

3. Study the use of other assumptions about the behavior of the deformation mechanism over time. Forinstance, the use of a linear model for a variable time period or the use of non-linear models.

4. Study the feasibility of the use of corner reflectors as reference points in the radar images and as PSson dikes.

5. Study the possibilities of other radar satellites, such as RADARSAT-1, ALOS, TerraSAR-X and RADARSAT-2. Also cross interferometry (using images from different satellites with different acquisition geometry)have to be studied.

6. Study a pre-operational system.

7. Improve the algorithms of PS processing, especially for PS detection, atmospheric effect estimation, andquality assessment.


Appendix A

List of used datasets

In this appendix the datasets are explained which were relevant for the project. A division is made, based onthe importance of the datasets. The first dataset is the most important, whereas the last ones are convenientbut not really important to have. For each dataset there is also described what the expectation of these datais.

Radar datasets

Content: The radar datasets contain the processed persistent scattering data and the Multi Reflectivity Map(MRM).Example: See figure A.1Supplier: TUDelft

Reference frame: pixel coordinatesVector or raster: rasterWay of acquisition: ERS 1 and 2 satellite

Topographical map 1:10.000

Content: This is a detailed vector map made by the Topografische Dienst Kadaster; the topographic surveyagency of the Netherlands.Example: See figure A.2Supplier: Topografische Dienst Kadaster

Reference frame: RDVector/raster: vectorWay of acquisition: Aerial Photography

DTB-wet and DTB-dry

Content: These Digital Topographical Files (DTB) of the wet and dry infrastructure at scale 1:1000 formtogether the DTB2000. These datasets contain very detailed and precise information about the geometry ofdikes and highways. It also contains information about the altitude of the ground level and objects near thedikes. The DTB2000 is a vector map.

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80 APPENDIX A. LIST OF USED DATASETS

Figure A.1: Example radar data

Figure A.2: Example top10vectorwww.kartografie.nl

Figure A.3: Example DTB-wet www.geo-loket.nl

Figure A.4: Example lenght profile

Example: See figure A.3Supplier: This map is free for education purposes; it is available at Rijkswaterstaat; the Directorate Generalof public works and water management

Reference frame: RDVector/raster: vectorWay of acquisition: aerial photography + additional terrestrial measurements

Ground truth datasets

Content: For instance leveling, tachymetry or GPS data. This data can be provided in excel-sheets, lengthprofiles or Move3 files.Example: See figure A.4Supplier: The responsible agency for the maintenance of the dike. This can be Rijkswaterstaat or a water-board.Way of acquisition: leveling


81

AHN

Content: Height maps of the Netherlands, with a sampling rate of about once every 5 meter.Example: See figure A.5Supplier: Rijkswaterstaat; the Directorate General of public works and water management

Reference frame: RDVector/raster: rasterWay of acquisition: laser altimetry from airplane

Figure A.5: Example AHN www.ahn.nl

Figure A.6: Example geotechnical profilewww.geodatabank.nl

Figure A.7: Example soil map 1:50000www2.bk.tudelft.nl

Figure A.8: Example aerial photograph

Geotechnical Profiles

Content: These profiles show the structure of the subsurface of the dike and the underlying soil layers.Example: See figure A.6Supplier: GeodelftWay of acquisition: drillings

Soil map and Borehole measurements

Content: The soil map 1:50.000 only provides information about the first meter, borehole measurements con-tains very detailed information about the soil layers, but only for the borehole locations.


82 APPENDIX A. LIST OF USED DATASETS

Example: See figure A.7Supplier: In principle this dataset is owned by Alterra, but this data can also be viewed online at http://www.bodemdata.nl/Similar data can be retrieved at www.dinoloket.nl.

Reference frame: RDVector/raster: vectorWay of acquisition: auger points

Technical drawings

Content: Technical drawings of a dike give information about the structure of dike; cross profiles, informationabout the used materials, foundation, etc.Supplier: The responsible agency for the maintenance of the dike. This can be Rijkswaterstaat or a waterboard.

Aerial photography

Content: Aerial photography usually has a better resolution than satellite imagery. With this photo’s itbecomes very easy to get an overview of the situation on the case study locations.Example: See figure A.8Supplier: Most of the municipalities have for their maintenance work digital aerial photos. Also the Cadastreis a provider of digital aerial photography: see website: http://www.kadaster.nl/ . Also the whole Netherlandsis covered with high resolution aerial photography in Google Earth and you can find them at:http://www.vanuitdelucht.nl/. Another option to get aerial photographs is via www.beeldportal.nl.

Reference frame: pixel coordinatesVector/raster: rasterWay of acquisition: Aerial photography

Ground water level charts

Content: These time series show for some points the fluctuations in the ground water level.Supplier: These data is available at www.Dinoloket.nl.

Water levels IJsselmeer

Content: These time series show for some points the fluctuations of the water level in the IJsselmeer andMarkermeer.Supplier: One of the so called ’Dienstkringen’ of Rijkswaterstaat, like the IJsselmeerkring or go to the operatorsof the sluices at, for example, Kornwerderzand.


Appendix B

Background information Harlingen

The following appendix describes the background information of the case study performed at Harlingen. Thefirst part gives an overview of the history and the current situation of the area. After that there is a sectionin data, which data was used and how it was prepared so that it was ready for interpretation.

Introduction

One of the natural recources in the Netherlands is salt, this is rock salt (halite) and magnesium salt. Thesetypes of salt, that are about 300 million years old, can be found underground in certain layers or in pillars.Salt mining in the Netherlands is performed on a few locations; one of these salt mines is near Harlingen(Sexbierum) and is exploited by the Frisia Company. In Friesland salt has been extracted since 1995, this isdone at a record depth of 2800 meters.

The salt is extracted by injecting water that dissolves the salt; the substance that results from this is pumpedto the surface and dried [28]. In the underground salt layer caverns form because of the extraction. Due to thepressure and temperature at the depth of 2800 meters the salt behaves like a thick liquid. The consequenceis that the salt slowly flows into the extraction caverns, resulting in subsidence of the whole area with a speedof up to 20 to 40 mm a year for the case of Harlingen. Locally the absolute subsidence can be up to a fewdecimeters with a legally allowed maximum of 35 cm for the area near Harlingen.

Data

In this section some information is given about the datasets that where used for the case study of Harlingen.Also there is an explanation of what needed to be done to prepare the data for further interpretation.

Used data sets

The datasets used for this case study are:

1. PS-InSar data

2. Top10 vector

83

84 APPENDIX B. BACKGROUND INFORMATION HARLINGEN

3. Google earth

4. Subsidence data

Figure F.37 gives an impression of what this data looks like. Clearly visible is the subsidence bowl due to thesalt mining in the area. The dike lies on the edge of the subsidence bowl. All points on the dike appear to bespatially correlated. At first sight no there are no points which behave different than usual. The tables B.1and B.2 give an overview of all acquisition dates of the PS-InSAR data.

Satellite Orbit Date Btemp (days) B (m)E1 03910 (master) 14-Apr-92 0 0

E1 3910 14-Apr-92 0 0E1 4411 19-May-92 1638 35E1 4912 23-Jun-92 1952 70E1 5413 28-Jul-92 1110 105E1 5914 01-Sep-92 1790 140E1 6415 06-Oct-92 1952 175E1 6916 10-Nov-92 2732 210E1 7918 19-Jan-93 1509 280E1 8419 23-Feb-93 2079 315E1 8920 30-Mar-93 2877 350E1 9421 04-May-93 1596 385E1 9922 08-Jun-93 1671 420E1 10423 13-Jul-93 1924 455E1 10924 17-Aug-93 1811 490E1 11425 21-Sep-93 1990 525E1 11926 26-Oct-93 2277 560E1 12427 30-Nov-93 2798 595E1 19785 27-Apr-95 1751 1108E1 20286 01-Jun-95 1755 1143E1 20787 06-Jul-95 2382 1178E1 24795 11-Apr-96 1616 1458E1 25797 20-Jun-96 2349 1528E1 26298 25-Jul-96 2183 1563E1 40326 01-Apr-99 1836 2543E1 41328 10-Jun-99 2476 2613E1 44835 10-Feb-00 1357 2858E2 3118 24-Nov-95 2190 1319E2 3619 29-Dec-95 2134 1354E2 4120 02-Feb-96 1728 1389E2 4621 08-Mar-96 2612 1424E2 5122 12-Apr-96 1635 1459E2 6124 21-Jun-96 2436 1529E2 7126 30-Aug-96 2051 1599E2 8128 08-Nov-96 1765 1669E2 9130 17-Jan-97 2217 1739E2 10132 28-Mar-97 2384 1809E2 11134 06-Jun-97 1998 1879E2 12136 15-Aug-97 2179 1949E2 13138 24-Oct-97 2325 2019E2 14140 02-Jan-98 1740 2089E2 15142 13-Mar-98 1991 2159

Table B.1: Ascending stack, track 258, continued on next page


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Satellite Orbit Date Btemp (days) B (m)E2 16144 22-May-98 2709 2229E2 17146 31-Jul-98 1560 2299E2 18148 09-Oct-98 2261 2369E2 19150 18-Dec-98 1666 2439E2 20152 26-Feb-99 2495 2509E2 21154 07-May-99 1960 2579E2 22156 16-Jul-99 2392 2649E2 23158 24-Sep-99 1157 2719E2 24160 03-Dec-99 2809 2789E2 24661 07-Jan-00 1719 2824E2 25162 11-Feb-00 1201 2859E2 26164 21-Apr-00 2219 2929E2 26665 26-May-00 2480 2964E2 28168 08-Sep-00 2243 3069E2 29170 17-Nov-00 2424 3139E2 35182 11-Jan-02 1413 3559E2 35683 15-Feb-02 2014 3594E2 36685 26-Apr-02 1651 3664E2 37186 31-May-02 1682 3699E2 37687 05-Jul-02 2141 3734E2 38188 09-Aug-02 2157 3769E2 39190 18-Oct-02 2937 3839E2 40192 27-Dec-02 2698 3909E2 41194 07-Mar-03 2689 3979E2 41695 11-Apr-03 1272 4014E2 42697 20-Jun-03 1755 4084E2 43198 25-Jul-03 1749 4119E2 43699 29-Aug-03 2028 4154E2 44200 03-Oct-03 2138 4189E2 44701 07-Nov-03 2898 4224E2 45202 12-Dec-03 1555 4259E2 45703 16-Jan-04 1703 4294E2 46204 20-Feb-04 2147 4329E2 48208 09-Jul-04 1664 4469E2 49210 17-Sep-04 2878 4539E2 51214 04-Feb-05 2578 4679E2 52216 15-Apr-05 2394 4749E2 53218 24-Jun-05 1897 4819E2 54220 02-Sep-05 2690 4889E2 55222 11-Nov-05 1619 4959E2 56224 20-Jan-06 2427 5029

Table B.1: Ascending stack, track 258

Satellite Orbit Date Btemp (days) B (m)E1 04304 (master) 12-May-92 0 0

E1 4805 16-Jun-92 35 -159E1 5807 25-Aug-92 105 -199E1 6308 29-Sep-92 140 -269

Table B.2: Descending stack, track 151, continued on next page



Satellite Orbit Date Btemp (days) B (m)E1 6809 03-Nov-92 175 253E1 7310 08-Dec-92 210 -733E1 7811 12-Jan-93 245 -300E1 8312 16-Feb-93 280 -10E1 8813 23-Mar-93 315 -552E1 9314 27-Apr-93 350 5E1 9815 01-Jun-93 385 -982E1 10316 06-Jul-93 420 -1291E1 10817 10-Aug-93 455 -114E1 11819 19-Oct-93 525 10E1 12320 23-Nov-93 560 22E1 19678 20-Apr-95 1073 -420E1 20179 25-May-95 1108 -493E1 20680 29-Jun-95 1143 -1640E1 21181 03-Aug-95 1178 -137E1 21682 07-Sep-95 1213 -1643E1 22183 12-Oct-95 1248 299E1 22684 16-Nov-95 1283 -882E1 23185 21-Dec-95 1318 249E1 23686 25-Jan-96 1353 -286E1 24187 29-Feb-96 1388 143E1 24688 04-Apr-96 1423 -457E1 25189 09-May-96 1458 289E1 25690 13-Jun-96 1493 -983E1 26191 18-Jul-96 1528 -1E1 43225 21-Oct-99 2718 -328E1 44728 03-Feb-00 2823 -1065E2 1508 04-Aug-95 1179 -208E2 2009 08-Sep-95 1214 -1728E2 2510 13-Oct-95 1249 765E2 3011 17-Nov-95 1284 -1726E2 3512 22-Dec-95 1319 -100E2 5015 05-Apr-96 1424 -578E2 6017 14-Jun-96 1494 -1095E2 6518 19-Jul-96 1529 -258E2 7019 23-Aug-96 1564 -1252E2 7520 27-Sep-96 1599 -673E2 8021 01-Nov-96 1634 676E2 8522 06-Dec-96 1669 -1054E2 9023 10-Jan-97 1704 -555E2 10025 21-Mar-97 1774 -728E2 10526 25-Apr-97 1809 -935E2 11027 30-May-97 1844 -879E2 11528 04-Jul-97 1879 -806E2 12029 08-Aug-97 1914 -600E2 12530 12-Sep-97 1949 -535E2 13031 17-Oct-97 1984 -311E2 13532 21-Nov-97 2019 -267E2 14033 26-Dec-97 2054 -223E2 14534 30-Jan-98 2089 -730E2 15035 06-Mar-98 2124 -1175E2 15536 10-Apr-98 2159 -1057



87

Satellite Orbit Date Btemp (days) B (m)E2 16037 15-May-98 2194 -85E2 16538 19-Jun-98 2229 -35E2 17039 24-Jul-98 2264 -666E2 17540 28-Aug-98 2299 -286E2 18041 02-Oct-98 2334 280E2 18542 06-Nov-98 2369 322E2 19043 11-Dec-98 2404 -1524E2 19544 15-Jan-99 2439 -821E2 20045 19-Feb-99 2474 708E2 20546 26-Mar-99 2509 -1033E2 21047 30-Apr-99 2544 -892E2 21548 04-Jun-99 2579 260E2 22049 09-Jul-99 2614 -1129E2 22550 13-Aug-99 2649 668E2 23051 17-Sep-99 2684 -497E2 23552 22-Oct-99 2719 -675E2 24053 26-Nov-99 2754 -747E2 24554 31-Dec-99 2789 296E2 25055 04-Feb-00 2824 -580E2 25556 10-Mar-00 2859 -685E2 26057 14-Apr-00 2894 -592E2 26558 19-May-00 2929 -501E2 27059 23-Jun-00 2964 -1224E2 27560 28-Jul-00 2999 -702E2 28061 01-Sep-00 3034 278E2 28562 06-Oct-00 3069 -632E2 29063 10-Nov-00 3104 -402E2 29564 15-Dec-00 3139 399E2 31067 30-Mar-01 3244 838E2 32069 08-Jun-01 3314 -2121E2 32570 13-Jul-01 3349 -1147E2 33071 17-Aug-01 3384 -1594E2 33572 21-Sep-01 3419 -2336E2 34073 26-Oct-01 3454 -2143E2 35075 04-Jan-02 3524 -1024E2 35576 08-Feb-02 3559 -371E2 36578 19-Apr-02 3629 -1053E2 37580 28-Jun-02 3699 436E2 38081 02-Aug-02 3734 -1110E2 38582 06-Sep-02 3769 267E2 39083 11-Oct-02 3804 -80E2 39584 15-Nov-02 3839 -348E2 40586 24-Jan-03 3909 -1142E2 41087 28-Feb-03 3944 -42E2 42089 09-May-03 4014 -1483E2 42590 13-Jun-03 4049 -937E2 43091 18-Jul-03 4084 -456E2 43592 22-Aug-03 4119 195E2 44093 26-Sep-03 4154 541E2 44594 31-Oct-03 4189 -861E2 45095 05-Dec-03 4224 -1017E2 45596 09-Jan-04 4259 -560




Axis Ascending Descendingx-axis 57 -75y-axis 30 -29

Table B.3: Shift differences in meters

Axis Ascending Descendingx-axis 11.49 9.16y-axis 6.75 6.91

Table B.4: Standard deviation in meters

Satellite Orbit Date Btemp (days) B (m)E2 46097 13-Feb-04 4294 -303E2 46598 19-Mar-04 4329 62E2 47099 23-Apr-04 4364 -1252E2 47600 28-May-04 4399 -455E2 48101 02-Jul-04 4434 -75E2 48602 06-Aug-04 4469 -591E2 49103 10-Sep-04 4504 -420E2 49604 15-Oct-04 4539 38E2 50105 19-Nov-04 4574 -1470E2 50606 24-Dec-04 4609 -983E2 51608 04-Mar-05 4679 -623E2 52109 08-Apr-05 4714 -878E2 52610 13-May-05 4749 -354E2 53111 17-Jun-05 4784 30E2 53612 22-Jul-05 4819 -429E2 54113 26-Aug-05 4854 -1099E2 55115 04-Nov-05 4924 -1226E2 55616 09-Dec-05 4959 -747E2 56117 13-Jan-06 4994 -1043E2 56618 17-Feb-06 5029 -562

Table B.2: Descending stack, track 151

Data Preparation

The next sections are an explanation of the steps that were needed to be taken to combine the differentdatasets and transform them so that they could be interpreted.

Georeferencing The PS-Radar points have been georeferenced in 3 steps, as described in section 5.3

Table B.3 presents an overview of the magnitude of the offset in meters that needed to be corrected for bythe georeferencing.

Table B.4 presents the standard deviation of the shift in meters, for both the ascending and the descendingtrack. It can be seen that that inaccuracies remain in the order of 6 to 12 meters. Also visible is that thestandard deviations in the y-direction are significantly smaller than in the x-direction. This can be explained bythe fact that the pixel size is 2 x 10 meters, with the satellite flying approximately in y-direction this translatesinto a more accurate determination of the y coordinate.


Appendix C

Background informationKornwerderzand

The following chapter describes the background information of the case study performed at Kornwerderzand.The first part describes the history and the current situation of the area. Also an overview of the area is given.

Introduction

Kornwerderzand is a specific part of the Afsluitdijk, it is part of the primary water barrier system of theNetherlands but it also has other functions. It contains a small and a big sluice to let ships pass, and a seriesof scouring sluices called the ’Lorentzsluizen’. This controls the water level of the IJsselmeer together withthe ’Stevinsluizen’, the water from the IJsselmeer is shed into the Waddenzee. Kornwerderzand is also a smallvillage with about 26 inhabitants. It is part of the municipality of Wunseradeel belonging to the provinceof Friesland. Kornwerderzand is also of military importance because of its strategic position and its waterregulating function ([12] and [23]).

Figure C.1: Location of Kornwerderzand

Figure C.2: Aerial overview of Kornwerderzand

89

90 APPENDIX C. BACKGROUND INFORMATION KORNWERDERZAND

History of Kornwerderzand

In 1921 it was decided to build the Afsluitdijk, for a long time this decision was blocked by the departmentof war. A possible enemy from the east could use the Afsluitdijk to invade the province of Noord Holland.Because of this it was decided to build a system of defense-works on Kornwerderzand and on Den Oever.The construction works on Kornwerderzand were financed by the builder of the Afsluitdijk: RWS. In 1931 thebuilding works of the fortification of Kornwerderzand started and they were finished in 1934.

Figure C.3: Construction of the Afsluitdijk

During April 1939 the Dutch army started using the complex and in May 1940 there was heavy fighting againstthe Germans. Due to the effectiveness of the complex it was the only Dutch defense work that withstood theGerman assault. In 1943 three additional bunkers where built by the Germans. After the second World Warthe complex was discarded, in the 80’s the department of Defense wanted to get rid of it so it was handed overto the original builder: RWS. It was their intention to cover the bunkers with sand and make them inaccessiblebut, due to the efforts of an action group, the bunkers were restored and transformed into a museum. In 2001the defense-works of Kornwerderzand were declared a national Dutch heritage site.

Current situation

The law states that the status of the water barriers should be inspected at least once every 5 years. In themost recent inspection of the Afsluitdijk it did not pass the test [13]. Over nearly the entire length the heightof the dike is not sufficient, and the structures on the dike are not strong enough (this includes the locks andthe scouring sluice at Kornwerderzand).

Nearly all structures at Kornwerderzand date back from the construction of the Afsluitdijk, so by now theyare 85 years old. Due to the harsh circumstances (strong wind and salty water) it is understandable that thestructures are showing signs of deterioration. This is why RWS had decided to renovate the complex and buildanother series of scouring sluices further along the Afsluitdijk.

Data

Used data sets

The datasets used for this case study are:

1. PS-InSar data


91

2. Top10 vector

3. AHN

4. (Aerial photos/Google earth)

For a detailed overview of all acquisition dates of the PS-InSAR data, see table B.1 and B.2 in appendix B.

Data preparation

The next sections are an explanation of the steps that were needed to be taken to combine the differentdatasets and transform them into one coordinate frame so that they could be interpreted.

Georeferencing

The PS-Radar points have been georeferenced in 4 steps, as described in section 5.3 :

1. Determination of PS-point and probable scattering source

2. Determination of both coordinates

3. Calculation of shift in x- and y-components

4. Application of shift and verifying the result

In table C.1 there is an overview of the amounts of offset that needed to be corrected for by the georeferencing.

Axis Ascending Descendingx-axis -56 63y-axis -24 25

Table C.1: Shift differences

Choice of reference point

In the descending track the reference point was located near Breezanddijk. In the ascending track there were2 reference points, one near Workum and the other in the province of Noord-Holland. This is because thenetwork on the Afsluitdijk was very weak. This led to a bad determination of for instance the atmosphericeffects. A second reference point solved this problem.

The choice of reference point is not important if one only wants to determine relative deformation. Differencesbetween points in the same track can be identified and used to determine the deformation.

Statistical determination of deformation

A histogram can be made of the deformation rate in ascending and descending track of the whole datasetwhich contains Kornwerderzand. This leads to figure C.4 and figure C.6



Figure C.4: Histogram of deformation rates of thewhole dataset, ascending track

Figure C.5: Histogram of deformation rates of thewhole dataset, descending track

Figure C.6: Histogram of deformation rates ofKornwerderzand, ascending track

Figure C.7: Histogram of deformation rates ofKornwerderzand, descending track

The figures have an almost normal distribution, but it can be seen that the average is not zero. To getsome insight in the behavior of the radar points, some means were calculated. For both the ascending asthe descending track, the mean deformation is listed in table C.2. In the descending track, the deformation

track KWZ Total DifferenceAscending 0.3211 -0.3207 0.6418Descending -0.4582 -0.5177 0.0595

Table C.2: Mean deformation.

of the area of Kornwerderzand is comparable to the deformation of the entire image. In the ascending trackthis is not the case. Kornwerderzand shows an uplift (in the LOS of the satellite) of 0.64 mm/year comparedto the rest of the image. This is a significant difference, mainly because it is an average of more than 1000points. An actual uplift of the area of Kornwerderzand is unlikely. This leads to the assumption that theexplanation of this difference can be found in the quality of the reference point or in the quality of the networkin the ascending track. The reference point is probably not the problem, because the deformation in theascending and descending track seen over the whole image is more or less comparable. For this reason, weassume that the explanation of the difference is in the quality of the whole network. This is likely to occur,because the afsluitdijk consists of just one thin line of measurements enclosed by water. If this is the correctassumption, we should correct for the differences in the ascending track. We can do this by shifting all thevalues for deformation in such a way so that the average becomes zero. The disadvantage is that we makethe assumption that there is no subsidence in the area of Kornwerderzand. This is possible, since the averagedeformation in the descending track is comparable to the average deformation of the whole image, and thepart of the Frisian mainland that we use should be more or less stable. The remaining analysis is performed


93

with the new, shifted, data. Histograms of the deformation can be constructed. Only points on the island ofKornwerderzand are taken into account.

The irregularities in the data lead to difficulties in comparing both datasets. For this reason, we have decidedto set the mean deformation of both tracks to zero. This calculation step led to the overview of the data asvisualized in figure F.39.

In Matlab, this plot looks like the plot in figure F.40.

In figure F.40 the deformation rate is visualized. Triangles facing up are ascending points, triangles facingdown are descending points. A triangle gets a bigger triangle around it if its deformation rate is larger than 1mm/y. As discussed in chapter 5, these points will be adressed as points with significant deformation.


Appendix D

Background information Marken

In the following appendix the background information of the case study of Marken is described. As a startthere is an explanation of the history of the area of Marken and a detailed description of the dikes. Then theused datasets are mentioned and the data preparation is explained in detail.

Introduction

The island of Marken is not just a part of the primary dikes of the Netherlands; it is also a special part. Thisis because the island is of high importance in both cultural and historical point of view. This section gives abrief overview of the history and current situation of the island of Marken. For more information on historyand culture, see [9], [15], [10] and [6].

History

The first known documentation of the area around Marken is from the eleventh and twelfth century. Back thenthe wide peat areas, which are now part of the community Waterland, were reclaimed and used as farmland.At that time Marken was not an island, it was part of the mainland, which was widely stretched and includedeven a part of the present Markermeer. During the second half of the twelfth century there were many severestorms, which had high water levels and flooding as a result. Due to this superfluous amount of water, the seareclaimed a large part of the land. At this time, also the ground level was decreasing because of settlement ofthe peat layer due to the new use of parts of the mainland as arable land. In this period, the area of Markenwas not used as arable land, and therefore the ground level did not decrease as fast as the other parts of themainland and Marken became an island. In 1251, the island of Marken was owned by a monastery, which usedthe land for agriculture. This lead to subsidence of the island, because the peat layer started to compact aswell. In this time, the monks had good knowledge and experience in building dikes and they were the first tobuild a dike around the island.

In 1345 the monks lost their property and the island of Marken was claimed by the count of Holland, WillemIV. Under his command, the dikes around Marken were neglected and the area flooded more and more. Due tothe salt seawater, the silted area was not suitable for agriculture anymore and the citizens of Marken becamefishers. To keep their properties safe, the citizens started to build their houses on artificial hills, (”terpen” or”werven” in Dutch). Because of an increasing population, the houses were built very close to each other. Atpresent, these houses still remain.

When the Afsluitdijk separated the IJsselmeer from the North Sea in 1932, the need for the people of Marken

95

96 APPENDIX D. BACKGROUND INFORMATION MARKEN

to build on artificial hills was gone because the water level became stable due to a lack of tidal fluctuations.In 1957 the connection to the mainland was established, because the government had plans to reclaim landfrom the Markermeer and establish the Markerwaard. Also the Bukdijk at the northern part of the island ofMarken was designed for that purpose. But due to protests from nature conservationists the establishment ofthe Markerwaard was stopped and the Markermeer remained.

Current situation

Today, Marken is a part of the Netherlands that is not only well known by the Dutch people, it has also becomethe image of the Netherlands for foreign tourists. The location of Marken can be seen in figure D.1, the islandhas only 2000 inhabitants. The function of Marken as a tourist attraction beneficial for the economy, notonly the local economy of Marken but also the Dutch economy. But the economy is not the most importantfactor that makes Marken so special. More important is the cultural-historical value of the island. This makesrenovation and renewing difficult, because this is bounded by restrictions and regulations. Not only renovationof the objects on the island, but also renovation of the dikes has to be done conform cultural-historicalguidelines.

Figure D.1: Location of Marken [16].

Figure D.2: Old map of Marken [6].

A short investigation made clear that a part of the dikes is known to be in a bad maintenance state and thatthere are some issues concerning the responsibility of monitoring these dikes. RijksWaterStaat (RWS) wantsto hand this responsibility of the primary dikes over to the waterboard according to their national policy, butthe waterboard ”Hoogheemraadschap van Uitwaterende Sluizen in Hollands Noorderkwartier” is not willingto take over these responsibilities because of the poor state of the dikes. This prior knowledge about themaintenance state makes the island of Marken interesting for a case study.

Dikes

The dikes of Marken can be divided roughly into two zones, namely the dikes around the island of Marken(the ”ring dike”) and the dikes that should be part of the Markerwaard (the ”Markerwaard dikes”). They willbe treated separately in this section. An overview of the dikes of Marken can be seen in figure F.41.


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Figure D.3: Schematical cross-section of the ring dike of Marken

The ring dike

The ring dike has a history that goes way back in time. As stated in the general history, monks made thefirst dikes around Marken in the 13th century, but in the centuries after that these were badly maintained.Therefore after a dike failure, a new part of the dike was built more inland. This way of building made theshape of Marken change and therefore Marken lost a part of its surface area. This can be seen clearly whenan old map (see figure D.2) of the island is compared with a contemporary one.

The southern and western parts of the ring dike were built in the 17th and 18th century, the northern partwas reinforced in 1994. The complete ring dike consists mainly of sandy clay and has a height of about 1.7meter above NAP (the ground level of Marken is about -0.5 meter below NAP). On top there is a sand layerand on the sides there is a clay layer. To keep those two separated, there is a concrete border in between. Atthe inner slope of the dike this clay layer is covered with grass, at the outer slope it is covered with basalticrocks, see figure D.4. A cross section is sketched in figure D.3.

During the reinforcement in 1994 the northern part of the dike was widened and made higher. This wasaccomplished by making the clay layer broader and higher. The slope of the dike became less steep as well.The reinforcement started at the most eastern point of Marken, at the lighthouse. During the reinforcementthe decision was made that the dike had to be higher than previously thought. Therefore at the location 650meter from the lighthouse the dike is suddenly about half a meter higher, see figure D.4.

Figure D.4: Northern part of the ring dike ofMarken, 650 meter to the west of the lighthouse.

Figure D.5: Deformed protective cover at thesouthern part of the ring dike of Marken.

The southern part of the ring dike is really different from the northern part. At some locations it is clearlyvisible that the dike does not have its original symmetrical shape anymore. For instance the inner slope ismuch steeper than the outer slope, this is probably due to some high pressure on the outer slope. This canbe becaused by nipping ice or the pressure of the water of the Markermeer against the vulnerable old dike.Also the state of the protective cover of basaltic rocks at the outer slope is not as smooth as the one of thenorthern dike. It is clearly visible that some deformations have occurred in the past (see figure D.5).



The Markerwaard dikes

As stated in the general history, the building of the dikes that should be part of the Markerwaard started in1957. The connection of Marken with the mainland (the ”Kruisbaakdijk”) was established a sooner than thedike at the northern part of the island (the ”Bukdijk”). They are designed exactly the same: The unstablepeat layer in the subsurface was removed during the construction of the dikes and this gap was filled withsandy clay. The height of these dikes is about 2.7 meter above NAP, so they are higher than the ring dike.

The dike connecting Marken with the mainland is like the ring dike maintained by RWS. The Bukdijk is notmaintained at all, because it does not have a water blocking function. This maintenance consists of bigmaintenance works every five years and normal maintenance every year. But the weak spots in the southernpart of the ring dike are checked every week. During these big maintenance works new wave breaking rocksare put at the foot of the dike. Also they fill subsided parts of the pavement at the top of the dike with sandand check the border between the sand and clay. For the big maintenance works, the dikes are leveled aswell. The yearly normal maintenance is conducted in a visual way, looking for signs of possible deformationor instability. During this normal maintenance a large number of pictures of the dike is made in a systematicway, with a digital camera from the top of a car.

Data

The general case study methodology as described in the first section of chapter 5 is used as well for the casestudy of Marken. But because not all datasets are available for Marken in particular, the used methodologyfor Marken differs somewhat. Because of this reason the specific datasets used for Marken and the datapreparation are described in this section.

Used datasets

As described in appendix A, many datasets were collected in the context of the POSEIDON project. Unfor-tunately, not all of these datasets were available for all the case study locations. The following datasets areavailable for the case study of Marken:

• Radar data (MRM and PS-InSAR data)

• Top10vector

• AHN

• Leveling and GPS data (deformation- and horizontal measurements)

• Maps with geotechnical profiles

• Soil map and borehole measurements

• Water levels Markermeer

The soil map and borehole measurements are not used, because there is a better alternative available: Geotech-nical length profiles of the ring dike. Whereas the soil map describes the layering of the surface until themaximum depth of 1 meter below the subsurface, the geotechnical profiles describe the subsurface of the dikesup to a depth of 20 meters.

Another dataset that was available for the Marken case study was leveling data, which included a report ofa deformation study of the ring dike of Marken in 2002 (see [46]). In this research the markers on the ringdike were leveled (the actual leveling was conducted in 2001) and compared these measurements with older


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Ascending dataset Descending datasetUsed satellites ERS 1 and 2 ERS 1 and 2Date master image 17-Jan-1996 (orbit 03891) 10-Jan-1997 (orbit 09023)Time interval slave images 1992-2000 (not in 1994) 1992-2000 (not in 1994)

Table D.1: Characteristics PS-InSAR datasets Marken.

Ascending DescendingCorrection value in x direction 58 -39Correction value in y direction 41 9

Table D.2: Correction values georeferencing (in meters).

leveling measurements of 1994, 1996, 1997 and 1998. They also measured the ring dikes with GPS-RTK,where 4 reference stations were used.

The characteristics of the PS-InSAR datasets are summarized in table D.1. This table includes the usedsatellite for both ascending and descending dataset, but also the acquisition periods are given. For a detailedlist of the acquisition dates, see E.2 and E.3 in appendix E.

Data preparation

This section gives a description of the preparation of the PS-InSAR data. This includes the georeferencing ofthe PS-InSAR points and the choice of the reference point.

Georeferencing

For Marken the PS-InSAR points are georeferenced with the use of the Top10vector. This was the mostdetailed topographic map that was available for the Marken area. Table D.2 gives an overview of the estimatedcorrection values for all the ascending and descending PS-InSAR points.

Choice reference point

To make the ascending and descending PS-InSAR points comparable with each other, a different referencepoint is chosen at a location where PS-InSAR points give reflections from the same object. The new referencepoint is preferably a point that lays in a stable area. For Marken this reference point was not chosen on theisland itself but on the mainland. This because the number of available PS-InSAR points on the island ofMarken was not that high. There were no locations where it was clear that both ascending and descendingPS-InSAR points were reflections of the same object. Therefore the reference point is chosen on the flatroof of a building in Volendam. The new reference point is assumed to be stable. This is because the newreference point did not move much with respect to the old reference point. Furthermore, the deformationvalue is comparable with the other PS-InSAR points in its surrounding area, so there is spatial correlation.This makes it unlikely that the new reference point is an autonomous movement or noise. The radar datasetswere processed for a relatively small area, because the atmospheric effect could then be estimated in a betterway. Therefore it is assumed that the atmospheric effects are small.


Appendix E

Background informationNoordoostpolder

This appendix contains the background information of the case study conducted to the IJsselmeer dikes in theNoordoostpolder. It starts with an introduction of the Noordoostpolder, some historical aspects are covered,and a defense is given why this area is chosen. The next section provides a small introduction about thedikes in the Noordoostpolder. Here, the structure and previous maintenance works of the dikes are discussed.This is followed by an overview of the used data sets for this particular case study and a description of somerelevant aspects concerning the preparation of the datasets and the choice of the reference point.

Historical aspects

The Noordoostpolder is a part of the so called Zuiderzee Works. The Zuiderzee Works are a man-made systemof dams, land reclamation and water drainage works, and they are the largest hydraulic engineering projectundertaken by the Netherlands during the twentieth century. The project involved the damming off of theZuiderzee, a large, shallow inlet of the North Sea, and the reclamation of land in the newly enclosed waterbody by means of polders. Its main purpose was to improve flood protection and create additional land foragriculture.

Original plans for the works date back to the seventeenth century, but it took until 1916 when a severe floodstruck the Netherlands before the Dutch parliament finally agreed. This results in the so called Zuiderzeewetfrom 1918. In 1919 the Zuiderzee Works Department was set up. From 1920 to 1924 they worked on a smalldike, for testing purposes. After that a 40 ha test polder, called Andijk, was made from 1926-1927 in theZuiderzee as a test run for making the Wieringermeerpolder. The creation of this polder started in 1927.Originally the polder would have been created after the completion of the Afsluitdijk, but there was a severelack of agricultural ground in that time. So they decided to start earlier. Draining of the Wieringermeerpolderwas finished on 21 August 1930. After the construction of the Afsluitdijk, which was finished in 1932 theystart in 1936 with the preparation works for the Noordoostpolder. This polder, with a total area of about480 km, is in fact the first IJsselmeerpolder. In 1937 the building of the dikes was contracted. Two yearslater the dikes between Urk and Lemmer were closed, followed by the closing of the dike at the side of theprovince Overijssel near Vollenhove in 1940. After that, the draining works started, which ended in 1942. Atthe end of the Second World War, work was started on draining the Flevopolder, a polder with an area ofalmost 1000 km. Another large polder was planned in the Markermeer, creation of which was heavily debateduntil the plans were officially abandoned in the early 2000s. A new province, Flevoland, was created out ofthe Noordoostpolder and the Flevopolder in 1986, thereby completing the Works. For an overview of all theworks on the map, see figure E.1.

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102 APPENDIX E. BACKGROUND INFORMATION NOORDOOSTPOLDER

Figure E.1: The Zuiderzee Works [27].

Figure E.2: The locations where ground improve-ments are carried out [1].

The choice of this case study

A first look on the PS map shows a lot of PSs on the IJsselmeer dikes of the Noordoostpolder. Also it wasalready known that some parts of these dikes show a deformation with respect to other parts of this dike.However, still there was no conclusive explanation what is happening here. This open question lead to theselection of this case study.

The structure of the dike

According to [1] and [2], different types of dikes are built around the Noordoostpolder. Also the preparationworks differs for different areas. The dikes at the south of Urk, indicated with III and IV in figure E.2, arefounded on an improved ground layer. Here, the soft soil layer is excavated and replaced by a stable layer.Only a small part of the dike at the north of Urk is also founded on an improved ground layer.

The type of dike from Lemmer to Schokland is the same [2], so only this type of dike is discussed in thissection. Notice the difference in time between the two engineering drawings; [1] from 1937, [2] from 1955.In 1937 there was water on both sides of the dike, so also the inner slope had to be protected to preventerosion. In [1] it can be seen that the inner slope also contains some stone layers. In [2] these stone layersare not visible any more, so probably they were removed when the polder was completely drained in 1942. Infigure E.3, a cross section is of the dike is given, taken from [2]. Here it can be seen that the top layer ofthe dike, the top of the outer slope and the whole inner slope are covered by a clay layer with a thicknessof 0.30 meter. Below that clay layer, there is a thick boulder clay layer at the outer side of the dike, whichbecomes smaller to the top and the inner side of the dike. At the foot of the inner slope, the thickness of


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Figure E.3: Cross-section of the dike from 1956 [1].

this layer increases again. The dike is founded on a sand layer, which is also the material of the core of thedike. On the outer slope of the dike, different protective covers can be found. On the foot of the outer slope,the collar mattress (kraagstuk) can be found. This layer is on the boundary of water and land. Usually thisconsists of geotextile, with on top mats of willow branches. The whole collar mattress is covered by rubbles((stortstenen). The collar mattress prevents that the waves and water flow flush away the sand. So it protectsthe dike for erosion below the water level. Next to the collar mattress there is a sheet piling with a size of0.08 by 1.80 meter. Behind this sheet piling they put basaltic blocks of different sizes. Then there is anothersheet piling, with a size of 0.08 by 0.40 meter. This is the left boundary of a road, which is made of concretecolumns or blocks (not clearly indicated at the engineering drawing). The right boundary consists of a concreteborder with behind it again concrete columns of two different sizes. From that point, the remaining part ofthe outer slope, but also the top and the inner slope are covered with grass. Notice that [2] is an engineeringdrawing made for maintenance works. Especially the protective covers changed with respect to [1]. This kindof maintenance works done from time to time for different parts of the dike. In the next section an overviewis given of what is known about these kinds of works.

Maintenance of the dike

The dikes and polders in the IJsselmeer area were created by the Zuiderzee Works Department, which was alsoresponsible for the dikes until 1986. This department fell under the responsibility of the State. In 1986, theresponsibility for the dikes in the Noordoostpolder and Flevopolder was handed over to the province Flevoland.They established two waterboards, which became, among other things, responsible for the maintenance ofthe dikes. For the Noordoostpolder, this was done by the waterboard Noordoostpolder. In 2000 these twowaterboards merged into waterboard Zuiderzeeland which is currently responsible for more than 200 kilometersof dike. Due to the transfer of the responsibility in 1986 a completing program was carried out on the dikes,during the end of the eighties and begins of the nineties. Many details about these works and also previousmaintenance works are lost. This is because of the several reorganizations that have been taken place.Another reason is that all people from RWS involved in this completing program, retired on pension afterthe ends of the works, [Mr. J. Boezeman, waterboard Zuiderzeeland, oral communication, 30 October 2006].However, according to Boezeman, the main part of the maintenance works that was done before 1987 was thereinforcement of the protective cover, which tended to slide away. This can be seen clearly during a period ofhigh water. The parts of the dike where the cover was below the water level were indicated and repaired assoon as the water level decreased. Also from the completing program, some details are lost.

We have one engineering drawing from that time, March 1992, where some works are indicated, see [3]. Onthis drawing, some parts of the dike are indicated where a new sheet piling had to be placed and where theyput new rubles, see figure E.4.

One of the agreements between the province, waterboard and the State was that the State takes care thatthe dikes became according to the current safety norms. In 1989, the Minister of Transport, Public Worksand Water Management decided that the dikes of the Noordoostpolder and the Flevopolder had to resist anoverflowing of the IJsselmeer, under circumstances that occurs maximal once per 4000 years. This so called



Figure E.4: Locations where in 1992 a new sheet piling is placed in combination with a new layer of rubbles.The details can be seen in the small map, which show the outer slope of the dike.

’1/4000-norm’ is written in the law on the water barriers of the Netherlands (Wet op de Waterkering) in 1996.Not all the dikes fulfilled this new norm, so a dike enforcement program was executed, which is more or lessfinished for the Noordoostpolder.

Data

This section contains an overview of the used datasets for this project. The general expectations of thesedatasets are listed in section 5.3, the details of these datasets can be found in A. This description is followedby a table where the used radar images are listed.

The used datasets

Table E gives an overview of the used datasets for this case study. If necessary some remarks are made aboutthe use or availability.

The ascending and descending radar images, used during the processing are listed in table E.2 and table E.3.The dates of the first and last image for ascending orbit are 3 May 1992 and 6 December 2000 respectively,for descending orbit these dates are 25 August 1992 and 15 December 2000. As can be seen, there is a gap inthe dataset between December 1993 and April 1995. During that time interval, the ERS-1 satellite was usedfor other purposes. After 1996, the ERS-1 acted as a backup satellite, only activated for special occasions. In1995 the ERS-2 satellite, which is almost completely similar to the ERS-1, became operational. This satelliteis still operational, but has some problems with one of the gyroscopes, which makes that not all images areuseful.


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Dataset Remarks1. Radar data (ascending + descending orbit)2. Topographical map 1:10.000 (Top10vector)3. DTB (DTB2000) This dataset was only available for a small part of

the southern dike.4. AHN5. Validation datasets, like leveling data,tachymetry or GPS measurements

No validation datasets were available. According toMr. Boezeman [Mr. J. Boezeman, waterboardZuiderzeeland, oral communication, 25 October2006] the IJsselmeer dikes of the Noordoostpolderare never monitored in order to detect deformation.

6. Geotechnical profiles of the dikes The geotechnical profiles do not cover all the dikes.Only the dikes at the south of Urk, are fullycovered.

7. Engineering drawings A few engineering drawings related to the dikes areavailable. According to Mr. Boezeman, [Mr. J.Boezeman, waterboard Zuiderzeeland, oralcommunication, 30 October 2006], much is lostdue to several reorganizations.

8. Borehole measurements and Soil map (1:50.000) These datasets are used when no geotechnicalprofile was available.

9. Time series ground water level The locations of these time series cover the wholeNoordoostpolder. For the Noordoostpolder, assubset of the available data was made, based onthe measurement period of the radar.

10. Time series water level IJsselmeer There are time series available for differentlocations in the IJsselmeer. Here the time series isused from the station at Lemmer.

11. Orthophotos Orthophotos are only available for a small area.This limits the use of this dataset for visualizationpurposes.

Table E.1: Overview of the used datasets



Satellite Orbit Date Btemp (days) B (m)E2 03891 (master) 17-Jan-96 0 0

E1 04182 3-May-92 -1354 -1138E1 04683 7-Jun-92 -1319 -1284E1 05184 12-Jul-92 -1284 -898E1 05685 16-Aug-92 -1249 -68E1 06186 20-Sep-92 -1214 -85E1 06687 25-Oct-92 -1179 456E1 07188 29-Nov-92 -1144 896E1 07689 3-Jan-93 -1109 -413E1 08190 7-Feb-93 -1074 119E1 08691 14-Mar-93 -1039 729E1 09192 18-Apr-93 -1004 859E1 09693 23-May-93 -969 -869E1 10194 27-Jun-93 -934 -690E1 10695 1-Aug-93 -899 -893E1 11196 5-Sep-93 -864 -234E1 11697 10-Oct-93 -829 421E1 12198 14-Nov-93 -794 833E1 12699 19-Dec-93 -759 1048E1 19556 11-Apr-95 -281 -727E1 20558 20-Jun-95 -211 -19E1 21059 25-Jul-95 -176 -372E1 21560 29-Aug-95 -141 537E1 22061 3-Oct-95 -106 -402E2 02388 4-Oct-95 -105 -787E2 03390 13-Dec-95 -35 -313E2 04392 21-Feb-96 35 -140E1 24566 26-Mar-96 69 47E2 04893 27-Mar-96 70 80E1 25067 30-Apr-96 104 -821E2 05394 1-May-96 105 -762E1 25568 4-Jun-96 139 629E2 05895 5-Jun-96 140 718E2 06897 14-Aug-96 210 664E2 07899 23-Oct-96 280 -348E2 09903 12-Mar-97 420 55E2 10404 16-Apr-97 455 195E2 10905 21-May-97 490 -358E2 11406 25-Jun-97 525 45E2 11907 30-Jul-97 560 5E2 12408 3-Sep-97 595 189E2 12909 8-Oct-97 630 -479E2 14412 21-Jan-98 735 333E2 15414 1-Apr-98 805 414E2 15915 6-May-98 840 148E2 16416 10-Jun-98 875 115E2 17418 19-Aug-98 945 -121E2 17919 23-Sep-98 980 29E2 18420 28-Oct-98 1015 319E2 19422 6-Jan-99 1085 1010E2 21426 26-May-99 1225 -168

Table E.2: Ascending stack, track 029, continued on next page


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Satellite Orbit Date Btemp (days) B (m)E2 22428 4-Aug-99 1295 717E2 24432 22-Dec-99 1435 -583E2 24933 26-Jan-00 1470 189E2 25434 1-Mar-00 1505 68E2 26436 10-May-00 1575 261E2 27438 19-Jul-00 1645 -440E2 28440 27-Sep-00 1715 -262E2 29442 6-Dec-00 1785 -119

Table E.2: Ascending stack, track 029

Satellite Orbit Date Btemp (days) B (m)E2 09023 (master) 10-Jan-97 0 0

E1 05807 25-Aug-92 -1599 93E1 06308 29-Sep-92 -1564 367E1 06809 3-Nov-92 -1529 966E1 07310 8-Dec-92 -1494 492E1 08312 16-Feb-93 -1424 436E1 08813 23-Mar-93 -1389 489E1 09314 27-Apr-93 -1354 1106E1 09815 1-Jun-93 -1319 -707E1 10316 6-Jul-93 -1284 -818E1 10817 10-Aug-93 -1249 170E1 11819 19-Oct-93 -1179 772E1 12320 23-Nov-93 -1144 950E1 19678 20-Apr-95 -631 -104E1 20680 29-Jun-95 -561 -781E1 21181 3-Aug-95 -526 358E2 01508 4-Aug-95 -525 326E2 02009 8-Sep-95 -490 -964E1 22183 12-Oct-95 -456 634E2 03011 17-Nov-95 -420 -974E1 23185 21-Dec-95 -386 475E1 24187 29-Feb-96 -316 682E2 05015 5-Apr-96 -280 -155E2 06017 14-Jun-96 -210 -305E2 07019 23-Aug-96 -140 -682E2 08021 1-Nov-96 -70 1090E2 10025 21-Mar-97 70 1E2 11027 30-May-97 140 -250E2 12029 8-Aug-97 210 172E2 13031 17-Oct-97 280 150E2 14033 26-Dec-97 350 -39E2 15035 6-Mar-98 420 -525E2 16037 15-May-98 490 711E2 17039 24-Jul-98 560 -342E2 18041 2-Oct-98 630 689E2 19043 11-Dec-98 700 -944E2 20045 19-Feb-99 770 1220

Table E.3: Descending stack, track 151, continued on next page



Figure E.5: The windmills near the IJsselmeer dikes in the Noordoostpolder

Satellite Orbit Date Btemp (days) B (m)E2 21047 30-Apr-99 840 -157E2 22049 9-Jul-99 910 -122E2 23051 17-Sep-99 980 -160E2 24053 26-Nov-99 1050 197E2 25055 4-Feb-00 1120 -466E2 25556 10-Mar-00 1155 -23E2 26558 19-May-00 1225 550E2 27059 23-Jun-00 1260 -797E2 28061 1-Sep-00 1330 420E2 28562 6-Oct-00 1365 104E2 29063 10-Nov-00 1400 434E2 29564 15-Dec-00 1435 299

Table E.3: Descending stack, track 151

Preparation of the data

Along the IJsselmeer dike from Urk to Lemmer, the Dutch energy company Essent placed 25 windmills in1987 and another 25 windmills in 1991, see figure E.5. These windmills, acts like a kind of corner reflectors.In both ascending and descending datasets, almost all windmills are clearly visible. This is because they aresurrounded by grass, so the windmills are the only objects that remain coherent. These windmills are used forthe georeferencing of the radar data.

For that part of the dike, only the topographical map 1:10.000 (Top10vector) is available. In this mapthe locations of the windmills are indicated with a symbol. All the visible windmills in both ascending anddescending datasets are used for the georeferencing. Because of the sidelobes, the multi reflectivity map isused to identify the main lobes. After that the coordinates are extracted from both the radar data and theTop10vector. The mean shifts, for ascending and descending orbit, in North (North) and East (East) directionare given in table E.

The standard deviation of the differences between the ’true’ and translated coordinates represents the relativeprecision of the georeferencing between the translated radar data and the Top10vector. It can be clearly seenthat the precision is quite good, which is due to the reflection characteristics of the windmills. Notice that thePS is located somewhere in the resolution cell, which has a resolution of 2 by 10 meter. This explains why thestandard deviation is in the meter level. The difference in ascending and descending orbit is due to the usednumber of points. Because of the fact that the windmills are almost on the vertical, the relative precision is


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Nr. of usedpoints

∆East (m) σEast (m) ∆North (m) σNorth (m)

Ascending 18 57 2,61 36 1,29Descending 31 -60 1,61 13 1,47

Table E.4: Results of the georeferencing

better in North direction. The absolute precision is assumed to be equal to the precision of the Top10vector.

Choice of the reference point

The windmills give an excellent opportunity for the choice of the reference point. This is because of the factthat the windmills are clearly visible in both ascending and descending datasets. The windmills are foundedon a stable layer by piles with a length of 8 - 12 meter, depending on the subsoil layers, [Mr. C. van Driessen,Essent, oral communication, 27 October 2006]. On top of these piles, there is a concrete plate, where thewindmill is placed on. It is never monitored whether these windmills subsides or not. However, the expectationis that this is not the case and until now there are no indications that this expectation is not correct. It ispossible that the windmills subside because of a subsidence of the layer where the windmill is founded on.In that case, subsidence is not visible, because the surrounding also subside. But also here, there are noindications for subsidence. It is possible that the windmills move, because of wind. In a wind of gale force 8- 9, the top can deforms up to 0.5 meter. Under normal conditions, this deformation is not visible. For thiscase study, one of these windmills is chosen as a reference point.


Appendix FColor images

Figure F.1: Overflowing [41] Figure F.2: Wave overtopping [25]

Figure F.3: Nipping ice at the Houtribdijk, thedike between Lelystad and Enkhuizen [21]

Figure F.4: Piping [41]

Figure F.5: An example of a plastic horizontalsliding. Here, the dike of Wilnis, a small town30 km southeast of Amsterdam, slid meters aside.This happened during a long, hot period in thesummer of 2003. The dryness caused the peatdike to dry and therefore it became lighter. Thestrength of the dike appeared to be no match forthe water pressure. [7]

Figure F.6: An example of sliding of the innerslope: This happened in January 2004 near Stein,a town in the Southeast of the Netherlands. Inthis case, overflowing or wave overtopping did notcause the sliding of the inner slope, but a leakingwater pipeline caused saturation of the dike. [29]

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Figure F.7: Persistent Scatterers in the area ofHarlingen

Figure F.8: Radar data Harlingen

Figure F.9: Overall Model Test results in ascend-ing track (blue=accept, red=reject)

Figure F.10: Overall Model Test results in de-scending track (blue=accept, red=reject)

Figure F.11: Standard deviation of residuals fromlinear model, ascending track

Figure F.12: Standard deviation of residuals fromlinear model, descending track

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Figure F.13: Interesting areas at KornwerderzandFigure F.14: Zoom in on area of the bridge (esti-mated deformation in mm/year)

Figure F.15: Side of the bridge Figure F.16: Visible deformation cracks

Figure F.17: Zoom in on sluice area (estimateddeformation in mm/year)

Figure F.18: Overview of the North dike (esti-mated deformation in mm/year)

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Figure F.19: Overall Model Test results for as-cending track

Figure F.20: Overall Model Test results for de-scending track

Figure F.21: Standard deviation of residuals fromlinear model ascending track

Figure F.22: Standard deviation of residuals fromlinear model descending track

Figure F.23: Rejected points in OMT are repre-sented in black

Figure F.24: Accepted measurements

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Figure F.25: Locations of ascending and descend-ing PS-InSAR points of Marken.

Figure F.26: Persistent scatter locations casestudy Marken

Figure F.27: Result of applying the global overallmodel test for the ascending PS-InSAR data.

Figure F.28: Result of applying the global overallmodel test for the descending PS-InSAR data.

Figure F.29: Standard deviation of residuals fromlinear deformation model for the ascending PS-InSAR data.

Figure F.30: Standard deviation of residuals fromlinear deformation model for the descending PS-InSAR data.

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Figure F.31: Locations of leveling (in red), NAPreference points (in orange) and GPS measure-ments (in green) of RWS [46].

Figure F.32: Length profile with leveling measure-ments of RWS, November 1996 (in dark blue), De-cember 1997 (in pink), November 1998 (in yellow)and November 2001 (in light blue) [46].

Figure F.33: GPS measurements of RWS ofNovember 1996 (in dark blue), December 1997 (inpink), November 1998 (in yellow) and November2001 (in light blue) [46].

Figure F.34: The results of the detection step.

Figure F.35: The two groups of PSs for Case B.

Figure F.36: The results of the Overall ModelTest.

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Figure F.37: Overview of datasets

Figure F.38: Overview of radar data (estimateddeformation in mm/year)

Figure F.39: Overview of normalized dataset

Figure F.40: Normalized dataset in MatlabFigure F.41: Overview of the dikes and their de-formation rates from PS-InSAR.

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