Integrating microwave and hyperspectral remote sensing for estimating vegetation structure and biomass

  • Estimate subcrown and crown dimensions and relative vegetation densities from multibaseline, polarimetric interferometric radar (TOPSAR).
  • Estimate leaf area index and fractional forest cover from hyperspectral data (AVIRIS)
  • Combine the parameters estimated from each data type to extract 2- and 3-component LAD
  • Demonstrate a novel approach to estimating biomass from the extracted structure and LAD parameters
  • Validate all of the above remote sensing measurements with field measurements

The possibility of global, three-dimensional remote sensing of forest structure with interferometric synthetic aperture radar (InSAR) bears on important forest ecological processes, particularly the carbon cycle. InSAR supplements two-dimensional remote sensing with information in the verticaldimension. Its strengths in potential for global coverage complement those of lidar, which has the potential for high accuracy vertical profiles over small areas. InSAR derives its sensitivity to forest vertical structure from the differences in signals received by two, spatially separate radar receivers.Estimation of parameters describing vertical structure requires multiple-polarization, multiple-frequency, or multiple baseline InSAR. Combining InSAR with complementary remote sensing techniques, such as hyperspectral optical imaging and lidar, can enhance vertical-structureestimates and consequent biophysical quantities of importance to ecologists, such as biomass. Future InSAR experiments will supplement recentairborne and spaceborne demonstrations, and together with inputs from ecologists regarding structure, they will suggest designs for future spacebornestrategies for measuring global vegetation structure. Estimates of this3-D structure result from augmenting two-dimensional(2-D) remote sensing with vertical structure measurements

Abstract: Truehaft RN, Law BE, Asner GP. 2004. Forest Attributes from Radar Interferometric Structure and Its Fusion with Optical Remote Sensing. BioScience 54: 561-571