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kellndorfer_WE3.T05.4.pptx Presentation Transcript

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