n. ackermann - biomass retrieval in temperate forested areas with a synergetic approach using sar...
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N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 1
Nicolas Ackermann
Supervisor: Prof. Christiane Schmullius
Co-supervisors: Dr. Christian Thiel, Dr. Maurice Borgeaud
FSU Jena, the 30th November 2010
Biomass retrieval in temperate forested areas with Biomass retrieval in temperate forested areas with a synergic approach using SAR and Optical a synergic approach using SAR and Optical
satellite imagery: state November 2010satellite imagery: state November 2010
PhD Colloqium 2010
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 2
Context
Objectives
Application: Biomass retrieval in the Thuringian Forest (Germany) Test site and data Pre-processing Analysis of the data Biomass retrieval
Schedules
Presentation outlinePresentation outline
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 3
Biomass – Carbon assessment: 1/3 of land surface is covered by forests Temperate forests : ~1/4 of world’s forests =>
Pool of Carbon Kyoto Protocol: “quantify emission limitation
and reduction commitments”
ENVILAND2: Objective:
automated processing chain land cover products optical and SAR synergistic approach
Status ENVILAND1 : scale integration + spatial
integration (2005-2008) ENVILAND2: level 3 products (kick-off:
November 2008)
ContextContext
World forest distribution (National Science Foundation)
Temperate terrestial biome
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 4
ObjectivesObjectives
Forested areas in Thuringian Forest
SPOT-5 ALOS-PALSAR
Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery
Priorities: Algorithms simple and robust Algorithms spatially and temporally transferable Global /regional scale Automatisation
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 5
Fusionprocessing
Results
Validation
Methodology
Processing phasesProcessing phases
Biomass retrieval
Results
Validation
Methodology
Analysis of the data
Regions of interests
SAR and Optical data analysis
Ground dataanalysis
SAR data
Pre-processing of the data
Optical data
Ground data
Test site selection
Test site
Data availability
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
95%Completed: 80% 50% 40% 10%
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 6
Test site selectionTest site selection
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 7
Tree Species
Scots Pine (Kiefer)
European Larch
Norway Spruce (Fichte)
Oak
Sessile Oak
European Beech (Buche)
European Ash
Thuringia Forest (Germany) Surface: 110 km x 50 km Terrain variations
90% of forest over hilly areas range: 800m - 900m
Forest proprieties: main species: Scots pines, Norway
Spruce, European Beech large biomass dispersion
Climate cool and rainy frequently clouded
Peculiarities logging for forest exploitation Kyrill storm (February 2007)
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Freq
uenc
y
Stem Volume [m3/ha]
Stem Volume
25 km
Test siteTest site
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 8
Initial test site limitations Only contains Norway Spruce Not well covered by RapidEye and
PALSAR Not sufficiently reliable forest stands Mostly located topographic area
25 km
Extended test siteExtended test site
Extended test site overcomes these limitations
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 9
SAR data ALOS PALSAR (L-Band, 46 days) TerraSAR-X (X-Band, 11 days) Cosmo-SkyMed (X-Band, 1 day)
Optical data RapidEye Kompsat-2
Ancillary data DEM: SRTM 25[m], LaserDEM 5[m] Laser points (2004), Orthophotos (2008) HyMap (2008,2009) Forest inventory (1989-2009) Photos with GPS coord. (2009) Weather data Field work
Available Data (state November 2010)Available Data (state November 2010)
Interferometric coherence
SAR topographic normalisation, SAR analysis
SAR analysis, Forest inventory validation
Multispectral radiometric normalisation
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 10
Satellite data - Thuringia Forest test site (state November 2010)
Mission Sensor Radar-Frequence Beam Polarisation Incident
angle# scenes available
ALOS PALSAR L-Band FBS HH 34.3° 43
ALOS PALSAR L-Band FBD HH/HV 34.3° 58
ALOS PALSAR L-Band PLR HH/HV/VH/VV 21.5° 13
TSX TSX X-Band HS HH, VV 21°-45° 41
TSX TSX X-Band SL HH, VV, HH/VV 23°-45° 9
TSX TSX X-Band SM HH/HV, VV/VH 23°-45° 18
CSK CSK X-Band Himage HH 40° 12
RapidEye RapidEye R,G,B, Red-edge, NIR 25
Kompsat2 Kompsat2 R,G,B, NIR, PAN 6
Available Satellite DataAvailable Satellite Data
Total: 225 scenes
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 11
Available DataAvailable Data
Temporal overview satellite data
ALOS PALSAR FBS
ALOS PALSAR FBD
ALOS PALSAR PLR
TSX SM
TSX SL
TSX HS
CSK Himage
Kompsat2
RapidEye
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 12
Pre-processing of the dataPre-processing of the data
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 13
RapidEyeRapidEye
RapidEye, R, G, B, 13th June 2009 (atmosphere corrected)
Multispeectral data - RapidEye L1B -
Orthorectification(manual GCPs)
Orthorectified-Radiance
-[W m-2 sr-1 µm-1] -
Atmosphere correction
• Calibrated 16 Bit product [W m-2 sr-1 µm-1]
Atmosphere corrected
- Reflectance [%] -
• Orthoengine PCI Geomatica
• ATCOR PCI Geomatica• Sun/Surface/Sensor normalisation• Atmospheric corrections• Relief radiometric normalisation• Scaling
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 14
Validation(JM distance)
RapidEyeRapidEye
• Definiens ecognition• Multisegmentation (scale 10)• Brightness ratio ((Bmax-B)/(Bmax-Bmin))• NDVI
Clouds/Clouds shadow masking
Cloud/shadow masked- Reflectance [%] -
Radiometric refined- Reflectance [%] -
Hyperspectral data - HyMap L2 -
Atmosphere corrected
- Reflectance [%] -
Empirical line correctionMAD normalisation
• MAD and Empirical line correction are based on linear regressions
• Validate with Jeffries-Matusita distance (JM) => require a low spectral separability
• External reference data: HyMap 2008, 2009 (DLR)
Training ROIs
Testing ROIs
Reference refined- Reflectance[%] -
Validation(JM distance)
Testing ROIs
1.
2.
3.4.
5.
6.
Training ROIs(automatic)
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 15
RapidEyeRapidEye
RapidEye (25th Mai 2009)
R: NIRG: Red-edgeB: R
RapidEye – Clouds mask
RapidEye – Clouds shadow mask
Non forest elements can be neglected
• + Performs well the masking• - Manual approach for each scene
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 16
PALSAR / TSXPALSAR / TSX
Crown Optical depth considerations n coefficient takes different values according to the investigated surface In forested areas, n can be related to the crown optical depth, which
in turns depends of two physical parameters : Ke and Hc Ke can be a function of the tree species composition and the weather
conditions (frozen, humid, dry, etc.) Hc can be a function of the local slope and the crown height
Analysis methodology Define a reference and perform a sensibility analysis by comparing
the coefficent of variation (CV) for different environnemental conditions
Estimate the optimal n coefficient by iteration using as a criteria the minimum of CV
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 17
PALSAR / TSXPALSAR / TSX
Example Reference parameters Number of stands may influence the statistics (min fixed: 25-30 stands) Incident angle = 38.7[°]
Intensity Parameter Reference test1 test2 test3 test4 test5 test6 test7 test8 test9 test10 test11σ0 (Hc) Local slope θloc = θref θloc < θref θloc > θref θloc = θref θloc = θref θloc = θref θloc = θref θloc = θref θloc = θref θloc = θref θloc = θref θloc = θrefσ0 (Hc) Tree height 20-23 20-23 20-23 10-13 30-33 20-23 20-23 20-23 20-23 20-23 20-23 20-23σ0 (Ke) Tree struct N.Spruce N.Spruce N.Spruce N.Spruce N.Spruce Beech Scot pine N.Spruce N.Spruce N.Spruce N.Spruce N.Spruceσ0 (Ke) Weather dry dry dry dry dry dry dry humid frozen thaw dry dry
σ0 Stem Volume Dense Dense Dense Dense Dense Dense Dense Dense Dense Dense Sparse Denseσ0 Forest Layers 1 1 1 1 1 1 1 1 1 1 1 2 or 3
cv = 0.136754
Ga
mm
a n
ou
gh
t [
dB
] -
FB
S
Local incident angle [°]
= -7.6 [dB]
n = 1
Ga
mm
a n
ou
gh
t [
dB
] -
FB
S
Local incident angle [°]
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
cvmin = 0.135138n optimal= 0.21
= -7.7 [dB]
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 18
Weather dataWeather data
Weather data DWD: Deutsche Wetter Dienst Acquisition period: 2006-2010 Parameters: Precipitation, Snowdepth, Water-equivalent, Wind,
Temperature, Sunshine duration, relative Humidity Pre-processing
Collaboration with FSU geoinformatic institute JAMS (Jena Adaptable Modelling System) Software 2 temporal scales : daily / hourly
Weather data[ .xml ]
Daily outputgeneration
HourlyRegionalised
[ .txt ]
Daily[ raster ]
Hourly Inputconversion
Daily inputconversion
HourlyRegionalisation
DailySelected[ .dat ]
HourlySelected[ .dat ]
DailyRegionalisation
DailyRegionalised
[ .txt ]
Hourly outputgeneration
Hourly[ raster ]
JAMS Software
90m
Station 1
Station 2
Station 5
Station 3
Station 4
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 19
Weather dataWeather data
Weather parameters outputs Raster data
90m and 300m spatial resolution Initial site / extended site
Excel table Describe mean weather values of the
overlapping selected forest stands and satellite data
Figure depicting the raster data (31mar08 - 03apr08)
Temperature [°C]Precipitations [mm]
High: 36
0
High: 10
0
Table summarizing weather data (simplified version)
Sensor Acquisition-date Daily (4 days meteorological conditions) Hourly (4 hours meteorological conditions)
Frame T°air_mean [°C]
T°air_min [°C]
T°air_max [°C]
Precipitation [mm]
Humidity [%]
Sunshine [hrs]
Wind speed [m/s) T°air_mean
[°C]Precipitation
[mm]Humidity
[%]Wind speed
[m/s}PALSAR 02/04/2008 21:29 1000 5.7 3.1 9.1 20.3 81.7 2.1 3.9 2.9 2.8 93.9 4.7PALSAR 02/04/2008 21:29 1010 7.6 4.6 11.5 16.7 76.4 2.1 4.0 5.1 2.0 88.4 4.4
… … … … … … … … … … … … … …PALSAR 06/05/2008 21:33 1000 10.9 4.5 16.7 0.1 69.8 9.6 3.3 11.4 0.0 75.3 3.8
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 20
Analysis of the dataAnalysis of the data
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 21
Processing chart-flowProcessing chart-flow
SAR data - ALOS PALSAR, TSX -
InSAR Phase / Coherence
Optical data - RapidEye -
DEM
Weather data- Precipitation,
T°, Wind -
SAR backscatter
Spectral Reflectance
SAR backscatter
InSAR Phase / Coherence
InSAR Height, Bands ratio, Textur,
Thresholding
Bands ratio, Textur,Thresholding
NDVI, ThresholdingSpectral Reflectance
Forest/non Forest Tree speciesCrown cover
Forest/non Forest Forest layersTree Height
Forest/non Forest Tree speciesCrown cover
IWCM
WCM
Biomass map
Pre-processing Algorithms to retrieve biophysical parameters
Algorithms to retrieve Forest biomass
Data analysis Biomass retrieval
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 22
RapidEye preliminary investigationsRapidEye preliminary investigations
RapidEye (R,G,B, Red-edge, NIR) – Test site Schmiedefeld
Color composite: R (NIR), G (Red-edge), B (R)
RE R, Red-edge, NIR, 5m, 13th June 2009
Tree species compositionRed: European BeechBlue: Norway Spruce
- The forest stands are well overlapping over the satellite image.
- Good separation between Beech and Spruce with a higher reflectance for Beech.
- Generally, very high reflectance in Red-edge and NIR for open area (grass).
- Urban show more reflectance in R than the other surface, which depicts the bright blue color.
- The wavelength are, as expected, absorbed by water in R, Red-edge and NIR channels (Dark blue).
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 23
RapidEye preliminary investigationsRapidEye preliminary investigations
RapidEye (R,G,B, Red-edge, NIR) – Test site Schmiedefeld
RE B, G, R, Red-edge, NIR, 5m, 13th June 2009
- The reflectance can be better differenciate for the different classes in high wavelength spectrum (Red-edge, NIR channel).
- Open area, Beech and Spruce have respectively ~60 [%],~40 [%] und ~20 [%] reflectance in NIR => potential of discrimination of these classes
- Slight differences bewtween signatures from low stem volume in comparison to high stem volume => maybe lead to a small sensitivity to forest biomassWavelength [nm]
Ref
lect
ance
[%
]
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 24
Stem volume [m3/ha]
RapidEye preliminary investigationsRapidEye preliminary investigations
RapidEye (NIR)
RE NIR, 5m, 25th September 2009
- Important physical considerations:
• Tree structure : shadow and additive reflectance
• Tree species composition: chlorophylle pigments
• Abiotic factors : soil moisture, air relative humidity, atmosphere effects
- Little negative linear correlation between RE NIR and stem volume for Beech (r2=0.25), Spruce (r2=0.1) and Pines (r2=0.04)
- The dispersions of the points are relatively homogeneous. Islotated high and low reflectance values are still occuring => clouds and clouds shadow => affect the statistics
- Good separation of Norway Spruce and Beech.
Ref
lect
ance
[%
] –
RE
NIR
ReflectanceBlue: Norway Spruce (S)Yellow: European Beech(B)Red: Scot Pine (P)
R2S=0.10
R2B=0.25
R2P=0.04
Y(x) = A * x + B
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 25
ALOS PALSARALOS PALSAR
ALOS PALSAR coherence
Stem Volume [m3/ha]
Inte
rfe
rom
etr
ic C
oh
ere
nc
e
Fra
me
1F
ram
e 2
R2S=0.19
R2B=0.038
R2P=0.044
R2S=0.10
R2B=0.009
R2P=0.009
R2S=0.22
R2B=0.012
R2P=0.06
R2S=0.35
R2B=0.12
R2P=0.08
R2S=0.36
R2B=0.15
R2P=0.088
R2B=0.002
R2S=0.29
Y(x) = A * x + B
Spatial baseline
Precipitations:23jul09: 28.6mm07sept09: 3.9mm
- Little negative correlation between ALOS PALSAR coherence and Stem Volume
- Higher coherence and higher correlation for Spruce in comparison with Beech and Pines (branches structure differs but stem volume distribution also)
- Weather effect (precipitations) and high perpendicular baseline can affect the correlation and the level of coherence
PALSAR FBD, 38.7°, HH, A, 25m
Frame location
1 2
Interferometric coherenceBlue: Norway Spruce (S)Yellow: European Beech(B)Red: Scot Pine(P)
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 26
Biomass retrievalBiomass retrieval
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 27
3. 5.
ALOS PALSARALOS PALSAR
ALOS PALSAR coherence – multitemporal approach
25% stands - Training -
SANTORO et al., 2000; SANTORO, et al., 2002b
5.
4.
3.
2.
1.
Linear Non-linearCoherence stack
Select andfit model
Scatterplot + model
Inverse modeland retrieve Stem volume
Estimated Growing stock
Volume
Compute RMSEand weights
Weights
75% stands - Testing -
Compute Growing Stock volume map
Growing stock Volume map
1., 2.4.
Forest inventory
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 28
ALOS PALSARALOS PALSAR
ALOS PALSAR coherence – Growing stock Volume map
Frame location
1 2
- Similarly to spatial averaging, the multitemporal combination act as a filter and decreases the noise.
- RMSEi>200 [m3/ha] is very high, in particular due to the high dispersion of the coherence. The methodology should be tested for each species separately and by inversing testing and training stands.
- Water and urban can be recognized, with respectively low (dark green) and high (gray) coherence
PALSAR FBD, 38.7°, HH, A, 25m
Multitemporal coherence biomass map
RMSE>200 [m3/ha]
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 29
Field campagn 2010Field campagn 2010
Forest campagn objective: collect information on the undergrowth in order to
interpret some of the obtained results Focus on low stem volume forest stands
Analysis of the dataTest site selection Pre-processing of the data Biomass retrieval
Undergrowth in a young regenerating forest stand
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 30
Schedules – next stepsSchedules – next steps DECEMBER-JANUARY
Data analysis:
- Process SAR intensity and coherence 2010
- Validate obtained results using ancillary data (weather, forest campagn)
Pre-processing:- Complete pre-processing Multispectral data
- Pre-processing weather parameter snowdepth and water equivalent
JANUARY-APRIL Data analysis:
- Complete analysis multispectral data
- Complete analysis SAR data
Modeling:- Develop modeling approach for SAR data
APRIL-AUGUST Fusion:
- Develop fusion approach for SAR – Multispectral data
- Complete modeling with the SAR data
PhD Dissertation:- Final results
- Papers
N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 31
Thuringia Forest – July 2010
Vielen Dank für Ihre Aufmerksamkeit!