1. Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery Nicolas Ackermann Supervisor: Prof. Christiane Schmullius Co-supervisors: Dr. Christian Thiel, Dr. Maurice Borgeaud Jena, the 11th June 2009

2.  Context  Objectives  Application: Biomass retrieval in the Thuringian Forest (Germany)  Test site selection  Pre-processing of the data  Analysis of the data  Biomass retrieval  Fusion  Schedules Presentation outline Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules N.A - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 2

3. 3  Biomass – Carbon assessment:  1/3 of land surfaces are 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) Context Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 3 World forest distribution (National Science Foundation) Temperate terrestial biome

4. 4 Objectives Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 4 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 AutomatisationGlobal regional scaleRobust

5. Fusion processing Results Validation Methodology 5 Processing phases Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 5 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrieval Biomass retrieval Results Validation Methodology Fusion Analysis of the data Regions of interests SAR and Optical data analysis Ground data analysis SAR data Pre-processing of the data Optical data Ground data Test site selection Test site Data availability

6. 6 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 6 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion  Thuringia Forest (Germany)  Surface: 110 km x 50 km (5500km 2 )  Terrain variations  90% of forest over hilly areas  range: 800m - 900m  Forest proprieties:  main species: Scots pines, Norway Spruce, European Beech  large Stem Volume variance  Climate  cool and rainy  frequently clouded  Peculiarities  logging for forest exploitation  Kyrill storm (February 2007) Test site Thuringia Forest (Google TM Earth) 25 km Scots pines Norway Spruce European Beech

7. 7 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 7 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Available Data  SAR data  ALOS PALSAR (L-Band)  TerraSAR-X (X-Band)  Additionnal SAR data  Cosmo-SkyMed (X-Band, constellation of 4 satellites) ?  E-SAR (L-Band and X-Band, DLR campagns) ? MissionSensor Radar- Frequency BeamPol. Incident angle # Scenes # Scenes Overlapping Status ALOSPALSARL-BandFBSHH 34.3° 293received ALOSPALSARL-BandFBDHH/HV 34.3° 323received ALOSPALSARL-BandPLRHH/HV/VH/VV 21.5° 62received TSX X-BandHSHH 23° 168acquisition TSX X-BandSLHH/VV 45° 121acquisition TSX X-BandSMHH/HV, VV/VH37°162acquisition SAR data - Thuringia Forest test site

8. 8 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 8 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Available Data  Acquisition dates

9. 9 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 9 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Available Data  Optical data  RapidEye  Additionnal Optical data  Kompsat-2 ?  JAS (Push broom Digital Camera, Jena-Optronik) ? MissionSensorChannels# BilderStatus RapidEye RGB, IR, NIR (5 Channels) 8acquisition  Ancillary data  DEM: SRTM 25[m], LaserDEM 5[m]  Laser points (2004), Orthophotos (2008)  Ground data: In-situ data (1989-2009), photos with GPS coord. (2009), weather data

10. 10 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 10 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Pre-processing phases  SAR Data pre-processing  Calibration  Multi-looking  Geocoding  Normalization  Co-registration Slope Aspect? Normalization specific to forest regions: Volume scattering: a) Tilted surface facing the radar, b) flat surface, tilte surface opposite to the radar (Castel, 2001)  Ground data pre-processing  Forest stands selection  Forest stands buffer  Graphe correlation with Satellite data  Optical data pre-processing  Calibration  Atmospheric corrections  Topographic normalization  Co-registration

11.  Biomass retrieval  ALOS PALSAR  RapidEye 11 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 11 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Data analysis perspective  Forest identification  ALOS PALSAR  TSX  RapidEye  Species identification  TSX  RapidEye  Tree and vegetation density  TSX  RapidEye  Forest stress and chlorophyll activity  RapidEye ASAR WS Biomass map (Santoro, et al., 2006)

12. 12 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 12 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Regions of interest (ROIs)  ROIs definition  Land cover: Crops, Forest, Urban, Water  Forest category: Sparse, Dense  Forest type: Broadleaf, Needle  Forest species: Scots pines (Kiefer), Norway Spruce (Fichte), European Beech (Buche)  ROIs selection procedure  Orthophotos observations  Areas > 100 pixels (~6 ha)  Homogeneity (low variance intra-class)

13.  Multitemporal  PALSAR :  FBD : 3 - 9 scenes  FBS: 2 - 10 scenes  FBD - FBS: 5 - 16 scenes  TSX:  HS: 9 scenes  HS - SL: 9 - 10 scenes 13 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 13 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion SAR data analysis  Frequency  L-band vs X-band  PALSAR HH - TSX HH  PALSAR HV - TSX HV  Polarisation  HH vs HV  PALSAR HH - PALSAR HV  TSX HH - TSX HV  HH vs VV  TSX HH - TSX VV  VV vs VH  TSX VV - TSX VH  VH vs HV  TSX VH - TSX HV  Incident angle  Radiometric analysis  TSX 23° - TSX 37° - TSX 45°  Geometric distortions analysis  TSX 23° - TSX 37° - TSX 45° The data analysis takes into consideration comparable data, namely for an analyzed parameter between two sets of data, all other parameter of this data must remain the same.

14.  Multitemporal  RapidEye  7 scenes ?  Bio-physical parameters  RapidEye  Absorbed Photosynthetically Active Radiation (PAR)  Leaf Area Index (LAI) 14 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 14 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Optical data analysis

15.  Descriptive statistics  Frequency  Parameters correlations  Bio-physical analysis  Relative stocking  Forest growth 15 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 15 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Ground truth data analysis Understand the forest

16. 16 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 16 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Additional data analysis  Texture and Structure  Filters  TSX  RapidEye  JAS  Variogram  TSX  RapidEye  JAS  Bio-physical parameters  JAS  Height derivation  Absorbed Photosynthetically Active Radiation  Leaf Area Index  Bi-directional reflectance distribution function (BRDF)  InSAR  Coherence  PALSAR (35 days r.p.)  TSX (11 days r.p.)  Cosmo-SkyMed (~1 day r.p. or better)  E-SAR (~1 hour r.p. or better)  Interferometric Height  TSX  Cosmo-SkyMed  E-SAR  Image processing  Pixel-based segmentations  ISODATA, K-Means, Fuzzy K- Means, …  Object-based segmentations  Decision Tree, …

17. 17 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 17 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Biomass retrieval  Remote sensing systems  ALOS PALSAR  RapidEye  Processing  Empirical models  Linear regressions  Non-linear regressions  Semi-empirical models  Water Cloud Model (WCM)  Branching Model  … Satellite [-DN-] Ground data Stem Volume y = ax + b y = ae bx WCM (Attema and Ulaby (1978) Vegetation component Ground component

18. 18 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 18 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Fusion perspective  Map accuracy improvement  Biomass base map  Transferability concept  Spatial: clouds, mosaicing  Temporal: lack of data SAR Optical Possible cases 1.Optical image clear 2.Optical image cloud covered 3.SAR image clear 4.SAR image cloud covered 5.Superimposed Optical and SAR images clear 6.Superimposed Optical and SAR image cloud covered Quality Factor (max=1) 0,8 0,5 0,7 0,9 0,8 1. 2. 3. 4. 6. 5. t t Spatial transferability Temporal transferability Optical data SAR data

19. 19 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 19 Analysis of the dataTest site selectionPre-processing of the dataBiomass retrievalFusion Fusion methodology Fusion Segmentation – Oriented-object Data merge – Pixel-based Biomass product (SAR or Optical) Model combination Fusion Levels … … Optical Pre-processing Forest Biomass map SAR Pre-processing SAR - Pre-processed - Optical - Pre-processed - Automatic Efficient Robust Fusion Segmentation – Oriented-Object Data merge – Pixel-based Biomass product (SAR and Optical) Model combination Fusion Levels … … Fusion Segmentation – Oriented-Object Data merge – Pixel-based Biomass product (SAR and Optical) Model combination Fusion Levels … … SAR Optical - Segmented - x - Segmentation - Biomass NDVI Y SAR = cx + d σ0σ0 Biomass Y optisch = ax + b x - Model combination - Fusion Segmentation – Oriented-Object Data merge – Pixel-based Biomass product (SAR and Optical) Model combination Fusion Levels … … Optical - Biomass product - x SAR - Biomass product - - Forest Biomass map - Fusion Segmentation – Oriented-Object Data merge – Pixel-based Biomass product (SAR and Optical) Model combination Fusion Levels … … SAR x - Data merge - Optisch - Pixels - What?Where? When? How?

20. 20 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 20 1. Data pre-processing 2. Data analysis & Biomass retrieval 3. Paper review Fusion SAR data Optical systems Optical data SAR systems Forest parameters SAR data Optical data Forest stands JUNE-JULY AUGUST SEPTEMBER

21. 21 Idenfitication of forested areas in South-East China with satellite imageryAckermann Nicolas Context Objectives Application: Biomass retrieval in the Thuringian Forest (Germany) Schedules - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - N.A 21 Thank you for your attention! Thuringia Forest