Relationships between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites

摘要: Abstract Mapping and monitoring of leaf area index (LAI) is important for spatially distributed modeling vegetation productivity, evapotranspiration, surface energy balance. Global LAI surfaces will be an early product the MODIS Land Science Team, requirements validation at selected sites have prompted interest in accurate mapping a more local scale. While spectral indices (SVIs) derived from satellite remote sensing been used to map LAI, type, related optical properties, effects Sun–surface–sensor geometry, background reflectance, atmospheric quality can limit strength generality empirical LAI–SVI relationships. In preliminary assessment variability relationships across types, we compared Landsat 5 Thematic Mapper imagery three temperate zone with on-site measurements. The differed widely location, physiognomy (grass, shrubs, hardwood forest, conifer forest), topographic complexity. Comparisons were made using different red near-infrared-based SVIs (NDVI, SR, SAVI). Several derivations examined, including those based on raw digital numbers (DN), radiance, top atmosphere atmospherically corrected reflectance. For one sites, which had extreme complexity, additional corrections geometry. Across all strong general relationship was preserved, increasing up values 3 5. but coniferous forest site, sensitivity low above forests, decreased highest because decreasing near-infrared reflectance associated complex canopy these mature old-growth stands. cross-site stronger than DN, or Topographic site altered some cases little effect Significant properties SVIs, independent evident. between around best fit this dataset suggests that accuracy development it desirable stratify by land cover classes (e.g., physiognomic type successional stage) vary SVI.