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

Mapping and monitoring of leaf area index (LAI) is important for spatially distributed modeling of vegetation productivity, evapotranspiration, and su rface energy balance. Global LAI surfaces will be an early product of the M ODIS Land Science Team, and the requirements for LAI validation at selected sites have prompted interest in accurate LAI mapping at a more local scale . While spectral vegetation indices (SVIs) derived from satellite remote se nsing have been used to map LAI, vegetation type, and related optical prope rties, and effects of Sun-surface-sensor geometry, background reflectance, and atmospheric quality can limit the strength and generality of empirical LAI-SVI relationships. In the interest of a preliminary assessment of the v ariability in LAI-SVI relationships across vegetation types, we compared La ndsat 5 Thematic Mapper imagery from thee temperate zone sites with on-site LAI measurements. The sites differed widely in location, vegetation physio gnomy (grass, shrubs, hardwood forest, and conifer forest), and topographic complexity. Comparisons were made using three different red and near-infra red-based SVIs (NDVI, SR, SAVI). Several derivations of the SVIs were exami ned, including those based on raw digital numbers (DN), radiance, top of th e atmosphere reflectance, and atmospherically corrected reflectance. For on e of the sites, which had extreme topographic complexity, additional correc tions were made for Sun-surface-sensor geometry. Across all sites, a strong general relationship was preserved, with SVIs increasing up to LAI values of 3 to 5, For all but the coniferous forest site, sensitivity of the SVIs was low at LAI values above 5. In coniferous forests, the SVIs decreased at the highest LAI values because of decreasing near-infrared reflectance ass ociated with the complex canopy in these mature to old-growth stands. The c ross-site LAI-SVI relationships based on atmospherically corrected imagery were stronger than those based on DN, radiance, or top of atmosphere reflec tance. Topographic corrections at the conifer site altered th SVIs in some cases but had little effect on the LAI-SVI relationships. Significant effec ts of vegetation properties on SVIs, which were independent of LAI, were ev ident. The variability between and around the best fit LAI-SVI relationship s for this dataset suggests that for local accuracy in development of LAI s urfaces it will be desirable to stratify by land cover classes (e. g. physi ognomic type and successional stage) and to vary the SVI. (C) Elsevier Scie nce Inc., 1999.