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  1. 1. REGIONAL TO GLOBAL SCALE MAPPING OF FOREST HEIGHT, BIOMASS AND CARBON FROM MULTI-SOURCE SATELLITE AND FIELD DATA<br />Josef Kellndorfer <br />Alessandro Baccini, Oliver Cartus, Scott Goetz, Nadine Laporte, Richard Houghton, Wayne Walker<br />The Woods Hole Research Center<br />
  2. 2. Outline<br />The National Biomass and Carbon Dataset 2000<br /> Fusion of SRTM InSAR, optical EO products and optical data<br />Biomass mapping with ALOS PALSAR dual-polarization data<br /> Another kind of SAR/optical data synergy<br />
  3. 3. Principal Investigator: <br />Josef Kellndorfer<br />Woods Hole Research Center<br />Research Team:<br />Wayne Walker, Katie Kirsch, <br />Greg Fiske<br />Woods Hole Research Center<br />Elizabeth LaPoint, Mike Hoppus, <br />Jim Westfall<br />USDA Forest Service FIA Program:<br />Collaboration:<br />Dean Gesch, National Elevation Dataset, USGS<br />Collin Homer, National Land Cover Database 2001 / MRLC, USGS<br />Zhi-Liang Zhu, LANDFIRE, USGS<br />Funding and Support:<br />NASA Terrestrial Ecology Program<br />LANDFIRE<br />PCI Geomatics<br />Definiens Imaging/eCognition<br />Four year project to produce<br /><ul><li>Forest vegetation height
  4. 4. Biomass and
  5. 5. Carbon Estimates
  6. 6. Conterminous U.S.
  7. 7. First attempt at 30 m resolution ever</li></ul>J.Kellndorfer, National Biomass and Carbon Dataset 2000<br />
  8. 8. The Opportunity …<br />A “millennium” opportunity exists to combine SRTM and several national data sets:<br />National Land Cover Database 2001<br />Provides Landcover, Treecover, Imperviousness<br />MRLC Landsat ETM+ Datasets 1999-2002<br />National Elevation Dataset<br />Compiled from Topographic Survey data<br />Cohesive processing for the first time around 2000<br />USDA Forest Inventory and Analysis Data<br />Ca. 300,000 surveyed plots with forest attributes (including height, biomass) <br />
  9. 9. Shuttle Radar Topography Mission: Global Coverage in 11 Days<br />Source: USGS<br />
  10. 10. SRTM Vegetation Response<br />Mean Canopy Height<br />Mean Scattering <br />Phase Center Height<br />SRTM Resolution Cell<br />Mean Canopy Height<br />Mean Radar Measured Height<br />Ground Elevation<br />Surface<br />
  11. 11. SRTM Vegetation Signal Extraction<br />Per pixel measurements have typical SAR noise characteristics -> Need to develop noise reduction approach which optimizes the retrieval of vegetation height<br />
  12. 12. Improving Radar Radiometry<br />Example: Michigan Woodlots<br />C-band Difference Image<br />C-band Difference Image<br />Before Object-based Averaging<br />After Object-based Averaging<br />X-band Difference Image<br />X-band Difference Image<br />
  13. 13. Biomass<br />Predictor Layers<br />Height<br />Predictor Layers<br />Statistical Fusion of Field and Satellite Data<br />Validation<br />Predicted<br /> Biomass<br />Output<br />Predicted<br /> Height<br />Modeling:<br />RandomForest<br />For 66 ecoregions<br />SAR<br />Backscatter<br />InSAR<br />Height<br />Optical<br />Reflectance<br />Input<br />Elevation<br />Response<br />Variables<br />Reference Data:<br />US Forest Inventory and Analysis Plot Network<br />300,000 Plots at Full Implementation<br />Slope<br />Reference Data<br />DBH/Height<br /> -> Biomass<br />Landsat - National Land <br />Cover Data Base 2001<br />
  14. 14. NBCD 2000 - Basal-Area Weighted Height<br />
  15. 15. 11<br />PUBLIC DATA RELEASED April 20th AT<br /><br />
  16. 16. Model Variable Importance Analysis with randomForest<br />SRTM phase scattering center and derived height<br />
  17. 17. NBCD 2000 Height and Biomass Estimates Compared with USDA Forest Inventory (FIA) at Plot Level via Bootstrap Validation<br />NBCD Predicted Height vs. FIA Height<br />NBCD Predicted ALD Biomass vs. FIA ALD Biomass<br />
  18. 18. Multi-Scale NBCD Biomass Estimates Comparison with FIAEstimates<br />Hexagon Scale<br />[ Hex Size = ~650 km2<br />= ~ 160,000 ac, i.e.<br />In ideal case: ~ 25 FIA plots ]<br />N = 8139<br />NBCD<br />19 Mg/ha / 0.92<br />(RMSD/Corr.Coef.)<br />County Scale<br />N = 2635<br />NBCD<br />14 Mg/ha / 0.95<br />NBCD<br />
  19. 19. NBCD 2000 Carbon Stock estimates Compared with USDA Forest Inventory (FIA) State Level Estimates<br />
  20. 20. Update of NBCD with ALOS PALSAR?<br />NBCD represents a unique product because several 30 m remote sensing products were available for the same time frame<br />
  21. 21. USDA project: Towards Spatially Explicit Quantification of Carbon Flux (2000-2007) in Northeastern U.S. Forests Linking Remote Sensing with Forest Inventory DataInvestigators: Kellndorfer, J., Cartus, O., Houghton, R. A., Walker, W. S.Collaboration: Maurizio Santoro, GAMMA RS <br />655 PALSAR FBD images for 2007/08<br />Multi-temporal coverage: 1-5<br />
  22. 22. Method<br />Automated Model training and inversion with the aid of the NLCD canopy density or the Vegetation Continuous Field maps<br /><ul><li>Identification of open and dense forest areas in the SAR imagery to calibrate the model with respect to changes in the backscatter signatures of forests due to, e.g., different weather conditions
  23. 23. Multi-temporal combination of single image biomass estimates</li></ul>Similar to what was developed for ENVISAT ASAR C-band data (Santoro et al. 2011, RSE) and for ERS-1/2 tandem coherence (Cartus et al., 2011, RSE) <br />
  24. 24. ALOS biomass map for 2007<br />Compared to NBCD<br />
  25. 25. When aggregating to county scale …<br />Vs. FIA county carbon statistics<br />Vs. NBCD 2000<br />
  26. 26. Conclusions:Two different types of SAR/InSAR/optical data synergy have beeninvestigated<br />Availability of very different data types was the key for the successful mapping of forest biophysical parameters over large areas<br />NBCD represents a unique product<br />At scales of >500 m, however, ALOS PALSAR Dual polarization appeared to allow reliable biomass estimates up to ~200 t/ha<br />