Geospatial Research at UCL –A presentation to EuroSDR Cardiff Oct 2008A presentation to EuroSDR, Cardiff, Oct. 2008

Jeremy MorleyDept Civil Environmental & Geomatic EngineeringDept. Civil, Environmental & Geomatic Engineering,UCL

University College London 20,000 students in 72 departments

• One of the top three UK universitiesuniversities– Largest research income

• 7th in Times Higher Education's7 in Times Higher Education s World Universities table, 2008

• Founded in 1826• Only Oxford and Cambridge are

older in EnglandFi t t d it l bilit• First to admit only on ability

• First to begin many subjects at universityuniversity– E.g. law, architecture, medicine

• First professor of ‘surveying’ p y gappointed 58 years ago

A Multi-Faculty University

• UCL is not a solely engineering/sciences universityIt 72 d t t bj t f L t• Its 72 departments cover subjects from Law to Biochemical Engineering and from Physics & Astronomy to Hebrew & Jewish Studies

• Similar span of departments doing "GeospatialSimilar span of departments doing Geospatial Research" Ai h i t h th b dth f h• Aim here is to show the breadth of research

• Apologies to all the uncited collaborating institutes p g gand individual researchers!

Geospatial Research Groups at UCL

• Dept. Civil, Environmental & Geomatic Engineering• Dept GeographyDept. Geography• Dept. Space & Climate Physics (MSSL)• CASA (Centre for Advanced Spatial Analysis)• Jill Dando Institute of Crime Science• Jill Dando Institute of Crime Science• UCL Chorley Institute• Centre for Polar Observation & Modelling• The Bartlett Faculty of the Built Environment• The Bartlett Faculty of the Built Environment• Institute of Archaeology

Geospatial Research Interests• Data creation: photogrammetry, remote sensing,

GPS surveying geodesy orbit modellingGPS, surveying, geodesy, orbit modelling• GIS data analysis methods: network analysis,

semantics & ontologies, space syntax• GIS systems: OGC/interoperability, SDSSGIS systems: OGC/interoperability, SDSS• Planetary mapping: DEM & orthos. creation &

l i iti i tanalysis; positioning systems• Environmental modelling: cryosphere, carbon g y p ,

dynamics, light/vegetation interaction, seabed• Applied GIS: urban modelling crime analysis• Applied GIS: urban modelling, crime analysis,

geodemographics, virtual worlds

A brief, selected, virtual tour of UCL groups & j tprojects…

Department of Civil, Environmental and G ti E i iGeomatic Engineering

S ffStaff• 39 academics

33 h f ll d i t t• 33 research fellows and assistants• 12 technicians

Students• ~75 PhD Students• ~75 PhD Students• ~120 MSc students• ~200 undergraduates• ~200 undergraduates

Three main research groupings:Three main research groupings:• Civil Engineering (incl. Environmental Engineering)• TransportTransport• Geomatics (9 academics)

Geographic InformationGeomatics

Geographic Information Science – Management of assets, such as land, property, and transportation infrastructure, planningtransportation infrastructure, planning and computer modelling of natural and urban environments

Photogrammetry, remote sensing and scanning – non-contact measurement technologies atcontact measurement technologies at scales from the micron to planet level, applications in terrain modelling, industrial measurement, heritage , gsector, city modelling

GPS, Geodesy and navigation –, y gpositioning on the surface of the Earth and in near-Earth space, measurement of plate tectonics, sea level, modelling of the gravity field and other reference surfaces, navigation for safety critical applications and mobile devices, time transfer

Photogram., remote sensing and scanning

Prof. Ian Dowman, Prof. Stuart Robson, J M lJeremy Morley

• Optag: RFID & photogram. integrated trackingOptag: RFID & photogram. integrated tracking• NASA Langley: dynamic structure monitoring• Laser scanning: terrestrial & small objects• Reference object properties in laser scanningReference object properties in laser scanning• Lava flow in situ close-range montoring• Sensor model for 3 line sensors using rigorous

orbital mechanics• Mosaics for determining terrain evolution

F i f hi h l ti ti l d t ith LiDAR• Fusion of high resolution optical data with LiDARfor building extraction

Engineering measurement facilities

• 10m x 5m x 2.5m metrology lab• Camera calibration facility (visible and thermal)y ( )• Kern ECDS & Leica Axyz• 5m optical rail with interferometer• Optical table with computer controlled motion and

rotation stagesM lti i i t d h t t i• Multi-camera imaging systems and photogrammetric software

• Metris K-Scan*• Metris K-Scan• Arius 3D Foundation system*

• Server array with 30TB of storage*Server array with 30TB of storage

Laser scanning•Arius 3D scanner – RGBArius 3D scanner RGB colour from three lasers, 80µm spot diameter, 100µm sampling interval, maximumsampling interval, maximum dimensional error 25µm.

•Metris K Scan –photogrammetrically tracked -2

0

2

4

6

4 9 14 19 24

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WhiteBlackR

OM

photogrammetrically tracked hand scanner

•Instrument testing: LeicaHDS Mensi GS1 Minolta 10

12

14

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18

cy

White

Neutral 8

Black

-14

-12

-10

-8

-6

-4

Offs

et (m

m BlackBlueGreenRed

rtesy

of

HDS, Mensi GS1, Minolta V900, Surphaser

•Include range variation with object colour measurement

2

4

6

8

10

Freq

uenc

Range from scanner to neutral 8 grey (m)

ges

cour

object colour, measurement of step edges and assessment with respect to known engineering surfaces

010 -8 -6 -4 -2 0 2 4 6 8 10

Distribution from Mean

ius

imag

known engineering surfaces•Influence of data processing•Project at JET fusion facility

Ari

NASA Langley

Solar sails Flapping flight

St t h d lStretched lens array

Parachute flight performance

Hawaii – Pahohoe Flows

1141oCControl points • ~ 15mm diameter white spheres (local craft shop), mounted on short lengths of wire (cut up bike spokes)mounted on short lengths of wire (cut up bike spokes) which could be inserted into crevices in the rock

Image acquisitiong q• Pair of 6MP Canon EOS 300D cameras with 28mm lenses synchronised together using a cable (~1 metre separation)

• 37 image pair sequence (1 image pair per minute)• 37 image pair sequence (1 image pair per minute)• Cameras pre‐calibrated in laboratory, with calibration refined by self calibration

Example change in profile

3 37 minute observation sequenceq

116 75

117.25

Altitude (m)0

116.25

116.7551015202530

115.751234 567891011

Horizontal distance (m)

3035

Building detection –Building detection –using LiDAR and Ikonos images (3)

UCL Building Map OS Building MasterMap©

Shufelt’s Building Extraction Metrics Results

Building Detection RateBranching Factor

93.92 %0.22 %

%Quality Percentage 77.94 %

Fusing LiDAR with digital imagery:g g g yRoof textures extracted automatically from the aerial images. Texture for vertical walls based on a ggeneric building facade

RADARSAT urban SAR image analysis for flood extent mappingflood extent mapping

C

A

DB

GNSS & G dGNSS & Geodesy

Prof. Paul Cross, Prof. Marek Ziebart,Dr Jonathon IliffeDr Jonathon Iliffe• EO and GNSS satellite force modelling• Centre for the Observation and Modelling of

Earthquakes and Tectonics (COMET)Earthquakes and Tectonics (COMET)• Seamless Positioning in All Conditions and

Environments (SPACE)• GNSS for Safety Critical Transport ApplicationsGNSS for Safety Critical Transport Applications• City Models for GNSS Availability and Multipath

St diStudies• Bear Ethology Around Romania (BEAR)

Snake GridProjection that keeps scale factor near unity along a chosen sinuous t d li li i t th d ftrend line – eliminates the need for scale factor and height corrections on

i i j tengineering projects.

Software developed for commercial puse in collaboration with UCL Business.

VERTICAL OFFSHORE REFERENCE FRAMES

EquipotentialEquipotentialODNODNODNODN

Local levellingLocal levellingMean sea levelMean sea level

“True” geoid“True” geoid

Local levellingLocal levelling

True geoidTrue geoid

CD1CD1

22CDCD

OSGM02OSGM02

ETRFETRF

22CDCD

VERTICAL OFFSHORE REFERENCE FRAMESSponsored by the UK Hydrographic Office

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VORF integrates tidal models, satellite altimetry, tide gauge data, GPS observations, and

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geoid models, to derive the position of Chart Datum in ETRF89.

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# ATT stations (secondary)# ATT stations (primary)$ PSMSL stations

# ATT stations (secondary)

Design of a navigation and communicationsDesign of a navigation and communications system for manned landings on Mars (ESA)• One year study covering space-to-

surface and surface-to-surface i i i d i ipositioning and navigation

technologies• System design incorporates micro• System design incorporates micro-

miniaturised atomic clocks, INS and communication system overlay ranging technologies

• First engineering use of HRSC M DEMMars DEMs

• Single orbiter used to develop landing site cartographic andlanding site cartographic and navigation control using single differenced phase observations

GIS research in UCL CEGE

Dr. Roderic Béra. Dr. Tao Cheng,Dr. Muki Haklay, Jeremy Morley

• Graph theory applied to geographical networks• Interoperability, WebGIS, mashups, communityInteroperability, WebGIS, mashups, community

mappingS ti & t l i• Semantics & ontologies

• Multi-scale spatio-temporal data modelling, p p g,analysis and reasoning

• Integration with environmental models• Integration with environmental models• HCI theory applied to GIS usability

Knowledge discovery in topographic d t bdatabases

OS d t hi d d t• OS produces topographic maps and data• OS wish to diversify their products. This can be done by

Thi d ti ll ti th i i i f ti it– Third parties collecting the missing information on site(problem: cost)

– Reusing what was already collected (preferred solution for cost eus g at as a eady co ected (p e e ed so ut o o costreasons)

• To some extent land use can be derived from the geometrical, topological and configurational information that is implicitly stored in OS DBTh i f thi j t i t fi d th l th t l t• The aim of this project is to find the rules that are relevant for the extraction of this information and to include them into a spatial ontology A reasoner is then used to infer landinto a spatial ontology. A reasoner is then used to infer land use from the topographic data.

Hierarchy of residential entities with typical titi lentities examples Block-

terracesDistrict-semis (dominant)

HousesTerraces Block-

semis

Residential Areas (suburbs)

Gardens

District-detached (dominant)

(suburbs)

S i d t h d

Out-building

Block-detached

Semi-detached

Roads

Detached District-terraces (dominant)

Block-mixed

District Aggregates

Primitive Aggregates

Housing Aggregates

Block Aggregates

Area Aggregates

Web 2.0, UGC and NMCAs

Personalised systems• Goes beyond interface designGoes beyond interface design

• Design of ontologies that can support multiple conceptualisations

• Aims:– To bridge mismatch between individual

conceptualisations,– bridging between concepts and system

To bridge between human and machine– To bridge between human and machine semantics

– To bridge gap between internal and external representations

– To develop a framework for context-based (spatial and temporal) semantics

Conceptualisation Comparison Toolbox forbased (spatial and temporal) semantics

• Methods:

Comparison Toolbox for comparing diverse semantics

in OWL-based user models– Formalising and schematising types of

semantic mismatchesC t i ti– Capturing user semantics

– Aligning ‘expert’ and ‘naïve’ ontologies

OGC GEOSS D t tiOGC GEOSS Demonstration –Disease Tracking Following Flooding (Mumbai)g g g ( )

Source: Mumbai Rain - Amit Kumar

http://www.ogcnetwork.net/node/167

FunOnTheNet

UCL CEGE / UCL Chorley Institute

• Community mapping public participationCommunity mapping, public participation• Urban & suburban town centre mapping• Usability engineering & HCI in GIS• Volunteered geographic information qualityVolunteered geographic information quality

assessments

The Chorley Institute vision

The UCL Institute of Geospatial InformationThe UCL Institute of Geospatial Information Sciences will act as a catalyst for interdisciplinary research at UCL b ‘spatiall enabling’ UCL’sresearch at UCL, by ‘spatially enabling’ UCL’sstrategic research objectives.

The Institute will achieve that by:• Providing the space and facilities for collaborationg p• Promote and incentivise projects that are aligned

with UCL strategic research objectives and whichwith UCL strategic research objectives, and which run by 2 or more departments.Promote collaborations with industry through• Promote collaborations with industry, through short collaborative secondments.

Noise mappingNew use of standard sound meters and paper maps for data collection in the area of London pCity Airport to collect the experience of noise, then the data is integrated in the GIS and a map is producedmap is produced. 

Map construction is done separately and requires knowledge of GISrequires knowledge of GIS

OpenStreetMap quality evaluationMap showing number of collaborators per Sq km grids – the principle is that you need more than one user to ensure qualitymore than one user to ensure quality

Spatial justice and OSMComparing OSM to the Index of MultipleComparing OSM to the Index of Multiple Deprivation shows that there is a bias towards wealthy places

Th l f 3D i i d tiThe role of 3D imaging and geomaticsin planetary explorationin planetary exploration

Jan-Peter Muller

Director, UK NASA RPIF Head of Imaging Group

Chair, CEOS-WGCV “Terrain mapping sub-group”Chair, ISPRS-IV/6 WG on “Global DEM Interoperability”Point-of-Contact, GEO task DA-07-01 on “Global DEM” Professor of Image Understanding and Remote Sensing

MODIS & MISR Science Team Member (NASA EOS Project)HRSC S i T M b (ESA M E P j )HRSC Science Team Member (ESA Mars Express Project)

Stereo Panoramic Camera CoI (ESA ExoMars rover)

Dept. Space and Climate Physics / Mullard Space Science Lab

HRSC-CTX-HIRISE : Mars Athabasca Vallis (8ºN, 156ºE)• Automated DTM production at multiple resolution using HRSC orthoimages as “map-Automated DTM production at multiple resolution using HRSC orthoimages as mapbase” to find common tiepoints with higher resolution CTX (6m) and even higher resolution HiRise (25cm) • Subsequent stereo processing allows DTMs of 50m (HRSC), 18m (CTX) and 0.7-5m q p g ( ) ( )(HiRise) to be produced

5m HiRISE stereo DTM, the refinement of 3 5 m HiRISE DTMof 3.5 m HiRISE DTM

400m MOLA DTM0.7m HiRISE stereo DTM, the refinement of 1.5 m HiRISE DTM

50m HRSC DTM 18m CTX DTM 3.5m HRSC DTM

How and what can we map from space?How and what can we map from space?Mars (upper) and Google Earth (lower)

© UCL 2007© UCL 2007

Perspective view of horizontal sedimentaryhorizontal sedimentary beds in cliff faces over Mars - Eberswalde crater (upper) and Egypt (lower)(upper) and Egypt (lower) at the SAME scale and resolution

Centre of Polar Observation and ModellingCentre of Polar Observation and Modelling

P f D Wi h D S LProf. Duncan Wingham, Dr. Seymour Laxon,Prof. Julian Hunt• Sea Ice Dynamics and Thermodynamics

D t il d M d l f S I D i– Detailed Models of Sea Ice Dynamics– Detailed Thermodynamics of Sea Ice

Optimisation of an Arctic Sea Ice Model using spaceborne– Optimisation of an Arctic Sea Ice Model using spaceborneestimates of ice thickness

• Earth's Ice Mass Fluxes• Earth s Ice Mass Fluxes – Antarctic Ice Mass Fluxes– Arctic Ice Mass Fluxes– Arctic Ice Mass Fluxes

• Topography and Buoyancy in Polar Atmosphere and OceanOcean

• ESA Cryosat / Cryosat 2 missions

Antarctic mass balance – thinning in WAIS

Jill Dando Institute of Crime Science

Spencer Chaineyp y

Beyond blobology – crime mapping researchHotspot map (KDE) Hotspots of significance (Gi*)

• The significance of where and when (spatial significance – Gi*)

E g understand how unusual the– E.g. understand how unusual the crime pattern is

– Space and time as a continuum rather than a snapshotrather than a snapshot

• Why (spatial regression - GWR)– E.g. relationship between why

crime happens where it doescrime happens where it does against other features

– Not just as a global relationship but as a local relationshipbut as a local relationship

• What if (spatial modelling - ABM)– E.g. if we target an intervention

to a particular place what impactto a particular place what impact may it have, including displacement and diffusion of benefit effects

Centre for Advanced Spatial Analysis,GIS in Dept GeographyGIS in Dept. Geography

P f P l L lProf. Paul Longley,Prof. Mike Batty,yDr. Andrew Hudson-SmithDr Alex SingletonDr. Alex Singleton

Surname profiler UK & now worldwideSurname profiler – UK & now worldwidepublicprofiler.org/worldnames

Singleton

Outreach: Media exposure

M T bMapTube

http://digitalurban.blogspot.com

My thanks to the various research groups at UCLUCL

• Dept. Civil, Environmental & Geomatic Engineering• Dept GeographyDept. Geography• Dept. Space & Climate Physics (MSSL)• CASA (Centre for Advanced Spatial Analysis)• Jill Dando Institute of Crime Science• Jill Dando Institute of Crime Science• UCL Chorley Institute• Centre for Polar Observation & Measurement• The Bartlett Faculty of the Built Environment• The Bartlett Faculty of the Built Environment• Institute of Archaeology