1. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 1 WSL Davos Colloquium Nicolas Ackermann Supervisor: Prof. Christiane Schmullius Co-supervisors: Dr. Christian Thiel, Dr. Maurice Borgeaud WSL Davos, 8th December 2011 Biomass retrieval in temperate forested areas with a synergic approach using SAR and Optical satellite imagery

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

3. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 3 WSL Davos Colloquium  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) Context World forest distribution (National Science Foundation) Temperate terrestial biome

4. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 4 WSL Davos Colloquium Forested areas in the Thuringian Forest Rapideye 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 Objectives

5. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 5 WSL Davos Colloquium Test site and data

6. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 6 WSL Davos Colloquium Test site  Thuringia Forest (Germany)  Surface: 110 km x 50 km  Terrain variations  Tree species composition  Scots pines  Norway Spruce  European Beech  Climate  cool and rainy  frequently clouded  Peculiarities  logging for forest exploitation  Kyrill storm (February 2007)

7. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 7 WSL Davos Colloquium Test site PineSpruce

8. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 8 WSL Davos Colloquium Test site Beech

9. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 9 WSL Davos Colloquium Test site Topography

10. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 10 WSL Davos Colloquium Test site Forest understory

11. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 11 WSL Davos Colloquium Test site

12. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 12 WSL Davos Colloquium  SAR data  ALOS PALSAR (L-Band, 46 days)  TerraSAR-X (X-Band, 11 days)  Cosmo-SkyMed (X-Band, 1 day)  E-SAR (L-Band, aerial system)  Optical data  RapidEye  Kompsat-2  HyMap  Ancillary data  DEM: SRTM 25[m], LaserDEM 5[m]  Laser points (2004),  Orthophotos (2008)  Forest inventory (1989-2010)  Photos with GPS coord. (2009)  Weather data  Field work Available Data

13. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 13 WSL Davos Colloquium Satellite data - Thuringian Forest test site MissionSensor Radar- Frequence BeamPolarisation Incident angle # scenes available ALOSPALSARL-BandFBSHH34.3°51 ALOSPALSARL-BandFBDHH/HV34.3°60 ALOSPALSARL-BandPLRHH/HV/VH/VV21.5°13 TSX X-BandHSHH, VV21°-45°41 TSX X-BandSLHH, VV, HH/VV23°-45°9 TSX X-BandSMHH/HV, VV/VH23°-45°18 CSK X-BandHimageHH40°24 RapidEye R,G,B, Red-edge, NIR25 Kompsat2 R,G,B, NIR, PAN6 Total: 247 scenes Available satellite data

14. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 14 WSL Davos Colloquium  Principle available parameters  Species  Age, Height, DBH  Basal area, Baumanteil, Relative Stocking, Bonity  Forest layers  Stem Volume  Acquisition date  Parameters for reliable stands selection  Storm damaged surfaces  Buffer (25m)  Tree coverage  Area (2ha)  Relative Stocking  Acquisition date  Orthophotos comparisons Data analysis & Modeling Forest inventory

15. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 15 WSL Davos Colloquium  Principle available parameters  Species  Age, Height, DBH  Basal area, Baumanteil, Relative Stocking, Bonity  Forest layers  Stem Volume  Acquisition date  Parameters for reliable stands selection  Storm damaged surfaces  Buffer (25m)  Tree coverage  Area (2ha)  Relative Stocking  Acquisition date  Orthophotos comparisons Data analysis & Modeling Forest inventory

16. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 16 WSL Davos Colloquium  Forest stands Low stem volume (0-100 [m 3 /ha]) High stem volume (500-700 [m 3 /ha]) Forest inventory

17. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 17 WSL Davos Colloquium Pre-processing

18. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 18 WSL Davos Colloquium Local incident angle Ground scattering area Topographic normalisation  Correction main components (Castel et al., 2001)

19. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 19 WSL Davos Colloquium  Optical crown depth (Castel et al., 2001) Volume scattering: a) Tilted surface facing the radar, b) flat surface, tilted surface opposite to the radar (Castel, 2001) Topographic normalisation

20. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 20 WSL Davos Colloquium Sensor orientation : 350° Sensor azimuth angle : +90° 0° PALSAR 34° HV Asc. 06may08 Normalised PALSAR 34° HV Asc. 06may08 Non normalised Gamma nought [dB] Aspect [°] Slopes oriented in Radar flight direaction High intensity for steep slopes facing radar. Topographic normalisation

21. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 21 WSL Davos Colloquium Topographic normalisation PALSAR 34° HV Asc. 06may08 Normalised Gamma nought [dB] Slopes away from the radar Slopes facing the radar Aspect [°] Overcorrection? Crown optical depth? Other effects?

22. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 22 WSL Davos Colloquium Topographic normalisation PALSAR 34° HV Asc. 06may08 Normalised PALSAR 34° HV Asc. 06may08 Normalised + Normalised with n coefficient Gamma nought [dB] Aspect [°]

23. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 23 WSL Davos Colloquium Analysis of the data

24. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 24 WSL Davos Colloquium Color composite: R (NIR), G (Red-edge), B (R) RE R, Red-edge, NIR, 5m, 13th June 2009 Tree species composition Red: European Beech Blue: Norway Spruce -Good separation between Beech and Spruce with a higher reflectance for Beech. RapidEye spectral reflectance  Visual interpretations

25. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 25 WSL Davos Colloquium TSX HS, 37.3°, HH, A, 10m, 12aug09 -Net contrast between Norway Spruce and European Beech Tree species composition Yellow: European Beech Red: Norway Spruce  Visual interpretations X-band backscatter

26. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 26 WSL Davos Colloquium L-band backscatter  Visual interpretations PALSAR FBD, 38.7°, HV, A, 25m, 20jul08 -Similar grey levels for the different stem volume. Stem Volume Yellow: 0-100 [m 3 /ha] (young stands) Blue: 100-400 [m 3 /ha] (mature stands) Red: 400-750 [m 3 /ha] (old mature stands)

27. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 27 WSL Davos Colloquium  Visual interpretations RapidEye RGB – 13jun09 TSX HS 28may10 - 08jun10 CSK Himage 28sep10 - 29sep10 - 1 day repeat pass - - 11 days repeat pass - X-band interferometric coherence

28. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 28 WSL Davos Colloquium L-band interferometric coherence A. B. C. intermediate coherence low coherence high coherence A.Forests: B. Crops: C. Urban: - 46 days repat pass - PALSAR HH 07sep09-23oct09  Visual interpretations

29. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 29 WSL Davos Colloquium Weather – TSX intensity Little increase of backscatter intensity with Precipitations Precipitation [mm] Temp [°] Wind [m/s] Series of TSX HS, 34.4°, HH, Asc. Acquisition date Gamma nought [dB] Precipitations

30. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 30 WSL Davos Colloquium Precipitation [mm] Temp [°] Wind [m/s] Series of PALSAR FBD, FBS, 34.6°, HH, Asc. Acquisition date Gamma nought [dB] frozen Snow + high Water equivalent frozen Weather - PALSAR intensity Temperature approaching 0 [°C] implies a decrease of the backscatter intensity

31. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 31 WSL Davos Colloquium Weather - PALSAR coherence Precipitation map PALSAR Coherence HH 23jul09_X_ 07sept09 A precipitation event highly affects the degree of coherence

32. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 32 WSL Davos Colloquium Urban Layover Precipitation [mm] Coherence Azimuth Weather - PALSAR coherence PALSAR FBD, 34.4°, HH, Asc.

33. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 33 WSL Davos Colloquium Biomass retrieval

34. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 34 WSL Davos Colloquium  Two approaches  K-Nearest Neighbor (non-parametric)  Regressions (parametric)  Investigations  PALSAR Intensity  PALSAR Coherence  Rapideye spectral reflectance Biomass estimation Assumption: stands with similar forest properties have also similar spectral characteristics

35. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 35 WSL Davos Colloquium Biomass estimation  Two approaches  K-Nearest Neighbor (non-parametric)  Regressions (parametric)  Investigations  PALSAR Intensity  PALSAR Coherence  Rapideye spectral reflectance Satellite [-DN-] Stem Volume [m 3 /ha] (Ground data) y = ae bx

36. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 36 WSL Davos Colloquium  Two approaches  K-Nearest Neighbor (non-parametric)  Regressions (parametric)  Investigations  PALSAR Intensity  PALSAR Coherence  Rapideye spectral reflectance Biomass estimation Satellite [-DN-] Stem Volume [m 3 /ha] (Ground data) y = ae bx

37. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 37 WSL Davos Colloquium  Coherence  The degree of coherence can be related to several factors, each expressing a specific source of decorrelation. Interferometric coherence The temporal decorrelation is related to the stability of the objects between the two acquisitions. The volume decorrelation is related to objects presenting a vertical extension. This factor is spatial baseline dependent.

38. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 38 WSL Davos Colloquium ALOS PALSAR coherence  Coherence versus Stem Volume Coherence seems to be related to the structure of the trees. Highest coherence for Spruce. r 2 Spruce =0.41 r 2 Beech =0.18 r 2 Pine =0.21 Interferometric cohreence Stem volume [m 3 /ha] - 46 days repat pass - PALSAR HH 07sep09-23oct09

39. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 39 WSL Davos Colloquium ALOS PALSAR coherence Precipitation on one of the interferomteric acquisition leads to deccorelation Precipitations [mm] PALSAR HH 23jul09 - 07sept09 Daily Hourly Acq. 1Acq. 2 28.6 5.1 3.9 0.0 Interferometric cohreence Stem volume [m 3 /ha] - 46 days repat pass - Norway Spruce  Temporal decorrelation: precipitations

40. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 40 WSL Davos Colloquium  Volume decorrelation: perpendicular Baseline (B n [m]) ALOS PALSAR coherence r 2 S = 0.00 r 2 S =0.21r 2 S =0.09 r 2 S =0.02 r 2 S =0.41 r 2 S =0.40 Interferometric coherence Stem volume [m 3 /ha] 46 days temporal baseline Norway Spruce An Increase of normal baseline increases coherence and correlation.

41. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 41 WSL Davos Colloquium ALOS PALSAR coherence  Training  Process stands mean values over coherence image and fit an empirical model  Remove outliers  Testing  Inverse model and derive Growing Stock Volume (GSV) map  Process stands mean values over GSV image  Calculate statistics (RMSE, accuracy matrix) and compute scatterplot  Products generation  GSV continuous values  GSV discrete values – classes  GSV discrete values – forest stands  GSV difference map – forest stands

42. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 42 WSL Davos Colloquium ALOS PALSAR coherence Interferometric Coherence Stem volume [m 3 /ha] it: 1. 0.51 2. 0.60 3. 0.65 5. 0.69 4. 0.68 9. 0.72 11. 0.72 10. 0.72 12. 0.72 6. 0.70 7. 0.71 8. 0.72 13. 0.72 14. 0.72 15. 0.72 r2  Training  Model:  Outliers: Norway Spruce

43. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 43 WSL Davos Colloquium ALOS PALSAR coherence  Testing  Inverse model and derive Growing Stock Volume (GSV) map  Process stands mean values over GSV image  Statistics (RMSE, accuracy matrix) GSV estimated [m 3 /ha] GSV Forest inventory [m 3 /ha] RMSE: 119 [m 3 /ha] 1:1 0.2*V ref -0.2*V ref + : 32% - : 26% Estimation: : 41%

44. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 44 WSL Davos Colloquium ALOS PALSAR coherence GSV discrete values – forest standsGSV difference map – forest stands  Products [m 3 /ha]

45. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 45 WSL Davos Colloquium ALOS PALSAR coherence  Products: GSV Difference map (Norway Spruce) Mostly overestimated Mostly underestimated + : 32% - : 26% Estimation: : 41% Norway spruce [m 3 /ha] Does the coherence or forest inventory induce spatial systematic errors in the estimates?

46. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 46 WSL Davos Colloquium ALOS PALSAR coherence  Modeling results of Empirical regressions (Norway Spruce) Error ≈ ±150 [m 3 /ha] Potential sources: - Site topography - Radar system - Estimation method - Forest inventory

47. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 47 WSL Davos Colloquium SAR data - ALOS PALSAR, TSX - InSAR Coherence Optical data - RapidEye - DEM Weather data - Precipitation, T°, Wind - SAR backscatter Spectral Reflectance SAR backscatter InSAR Coherence Bands ratio, Thresholding Spectral Reflectance Forest/non Forest K-NN Regressions Biomass map Pre-processing Algorithms to retrieve biophysical parameters Biomass map Spruce Biomass map All species Tree species Synergy / Fusion Information combination Summary - available information Biomass map Beech Forest/ non-Forest map Tree species map

48. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 48 WSL Davos Colloquium SAR data - ALOS PALSAR, TSX - InSAR Coherence Optical data - RapidEye - DEM Weather data - Precipitation, T°, Wind - SAR backscatter Spectral Reflectance SAR backscatter InSAR Coherence Bands ratio, Thresholding Spectral Reflectance Forest/non Forest K-NN Regressions Biomass map Pre-processing Algorithms to retrieve biophysical parameters Biomass map Spruce Biomass map All species Tree species Synergy / Fusion Information combination Summary - available information Biomass map Beech Forest/ non-Forest map Tree species map

49. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 49 WSL Davos Colloquium How can we create a biomass map using the entire available information? Summary – available information

50. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 50 WSL Davos Colloquium Fusion / Algorithms

51. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 51 WSL Davos Colloquium  Approach  The combination of different sensors can be achieved by several approaches. As part of this PhD and the project Enviland2, it was decided to focus the work on the fusion of different established products, such as a map of biomass or a mask forest/non forest.  The fusion and/or synergy would be performed where EO data are spatially overlapping.  The idea would be to obtain a final biomass map which is constituting the best potential result in regards to the initial data provided by the user.  Motivation  The chosen approach was motivated by its simplicity but also by its flexibility (different sources of biomass maps).  As the number of different sources of information/sensors have increased considerably these recent years, it is necessary to have an approach which allows the combination of the high amount of available data.  The combination of several datasets would allow to increase the accuracy of the biomass map, its spatial extension and its updated frequency. Fusion approach - motivations

52. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 52 WSL Davos Colloquium  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 Fusion approach

53. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 53 WSL Davos Colloquium Processing work-flow  IDL script processing steps 1.Input data and user parameters definition 2.Tiling for loop (tile) 3.Masks and quality flags establishment a.Forest/non-forest b.Tree species 4.Fusion/Synergy process a.Forest/non-forest b.Tree species c.Biomass 5.Masking endfor 5.Mosaicking

54. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 54 WSL Davos Colloquium 1.Input data and user parameters definition 2.Tiling for loop (tile) 3.Masks and quality flags establishment a.Forest/non-forest b.Tree species 4.Fusion/Synergy process a.Forest/non-forest b.Tree species c.Biomass 5.Masking endfor 5.Mosaicking Processing work-flow  IDL script processing steps

55. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 55 WSL Davos Colloquium Masks and quality flags establishment  Histogram Analysis Landcovers: Forest, Crops, Urban, Water Tree species: Spruce, Beech, Pine Classes Input data Coefficients of correlation Classes Input data Thresholds Occurence Gamma nought [dB] C(h) H(x) Gamma nought [dB] Difference histograms Cross-correlation h [dB] 010203040

56. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 56 WSL Davos Colloquium  Database LandcoversTree species Input data Thresholds Landcovers Input data Coefficients of correlation Tree species Masks and quality flags establishment

57. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 57 WSL Davos Colloquium  Database LandcoversTree species Input data Thresholds Landcovers Input data Coefficients of correlation Tree species Masks and quality flags establishment

58. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 58 WSL Davos Colloquium 1.Input data and user parameters definition 2.Tiling for loop (tile) 3.Masks and quality flags establishment a.Forest/non-forest b.Tree species 4.Fusion/Synergy process a.Forest/non-forest b.Tree species c.Biomass 5.Masking endfor 5.Mosaicking Processing work-flow  IDL script processing steps

59. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 59 WSL Davos Colloquium  Fusion rules  Merging for multitemporal datasets  Bands rationing  Synergy rules  Masks: min(correlation)  Biomass: min(RMSE)  Flag quality  Masks: score=(1-correlation)*100  Biomass: RMSE Fusion/Synergy process Input data 1, 2, 3 Input data 2 x y

60. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 60 WSL Davos Colloquium Final products  Forest/non-forest map 121 PALSAR intensities 16 PALSAR coherences 24 CSK intensities 12 CSK coherences Forest map

61. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 61 WSL Davos Colloquium Final products  Grass Flag quality and Crops Flag quality 121 PALSAR intensities 16 PALSAR coherences 24 CSK intensities 12 CSK coherences Grass_Flag [score]Crops_Flag [score]

62. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 62 WSL Davos Colloquium Final products  Urban Flag quality and Water Flag quality 121 PALSAR intensities 16 PALSAR coherences 24 CSK intensities 12 CSK coherences Urban_Flag [score]Water_Flag [score]

63. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 63 WSL Davos Colloquium  Tree species map - flag map Final products In progress !

64. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 64 WSL Davos Colloquium  GSV map Final products 121 PALSAR intensities 16 PALSAR coherences 24 CSK intensities 12 CSK coherences 15 Biomass maps GSV [m3/ha]

65. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 65 WSL Davos Colloquium  GSV Flag quality (RMSE) Final products 121 PALSAR intensities 16 PALSAR coherences 24 CSK intensities 12 CSK coherences 15 RMSE images GSV_Flag [m3/ha]

66. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 66 WSL Davos Colloquium Summary & Concluding remarks  A synergy approach was developped and implemented on IDL  The algorithm sort the useful information from the given input data  The final products are:  Forest/Non-forest map  Tree species map (Spruce, Beech)  Biomass map  The user can define:  Output product  Biomass classes  Spatial resolution, Tiles size, Required accuracy (RMSE and correlation)  Active/non-active ratios  The biomass maps can be evaluated using the flag quality indicator

67. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 67 WSL Davos Colloquium Schedules – next (last) steps

68. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 68 WSL Davos Colloquium Schedules – next (last) steps December-… Optical results Finalize Fusion script Products Validation PhD Dissertation: -Final results -Papers

69. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 69 WSL Davos Colloquium Temperate Forest (Germany) – October 2011 Thank you for your attention !

70. N. Ackermann - Biomass retrieval in temperate forested areas with a synergetic approach using SAR and Optical satellite imagery - 70 WSL Davos Colloquium Methods Empirical Models Semi-empirical Models Theoretical Models Pre-processing Biophysical parameters retrieval Forest biomass retrieval Forest Biomass Map + Quality flag Products Forest/Non Forest Tree species Density Forest layers Tree height Methods Bandsratio Texture Thresholds InSAR height NDVI Products Biomass Products SAR Intensity InSAR Coherence InSAR Phase Multispectral Reflectance Methods SAR Geocoding Interferometry Polarimetry Atmospheric correction Topographic normalisation Ancillary Data Forest inventory DEM Weather data Satellite data SAR Optical Data Processing flowchart Methods Merging Bands rationing Products combination Products Biomass map Forest map Tree species map Quality flags Synergy process