Use of ASTER Optical Indices to Estimate Spatial Variation in Tropical Seasonal Forests on the West Bank of the Mekong River, Cambodia
Forest ecosystem parameters related to the amount of evapotranspiration and rain interception are key elements to successful hydrological modeling. Thus, we evaluated ASTER (Advanced Spaceborne Thermal Emission and Reflection radiometer) reflectance bands and optical indices for qualitative and quantitative estimation of various characteristics of tropical seasonal forests. Ground conditions were measured in 14 sites in Kampong Thom Province, Cambodia, representing six major tropical seasonal forest types: dry evergreen forest, mixed evergreen-deciduous forest, dry deciduous forest, regrowth of dry evergreen forest, moist evergreen forest, and swamp forest. We performed a discriminant analysis to classify forest types using ASTER reflectance bands and optical indices. We used Visible and near infrared Radiometer (VNIR) and Shortwave Length Infrared Radiometer (SWIR) surface reflectance, four vegetation indices: NDVI (Normalized Difference Vegetation Index); SR (Simple Ratio); DVI (Difference Vegetation Index), and MSAVI2 (Second Modified Soil Adjustment Vegetation Index), and three water content indices: SRWI (Simple Ratio Water Index); NDWI (Normalized Difference Water Index); and LWCI (Leaf Water Content Index), for the discriminant analysis. ASTER image products were acquired on January 12, 2002 in the dry season. We also performed regression analyses to identify an optical index closely correlated with forest qualitative characteristics such as tree density, tree height, basal area, and leaf area index (LAI). Each forest type showed a distinctive pattern in reflectance bands, demonstrating that satellite images can potentially be used for regional forest type classification.
KeywordsNormalize Difference Vegetation Index Forest Type Leaf Area Index Normalize Difference Water Index Optical Index
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