A Simplified Procedure for a Large Scale LAI Inversion from High Resolution Satellite Data

This study is aimed at demonstrating the feasibility of the large scale LAI inversion algorithms using red and near-infrared reflectance obtained from high resolution satellite imagery. The algorithms are developed based on the principle commonly used for ground-based optical determination of LAI by assuming that high resolution remote sensing imagery is capable to distinguish shadows/gaps from canopy. Gap fraction was obtained from scaled difference of Normalized difference Vegetation Index (NDVI), Scaled Difference Vegetation Index (SDVI), and Modified Soil-Adjusted Vegetation Index (MSAVI) from SPOT 10 m pixel imagery. The sensitivity of the methodology was evaluated for spatial resolution effects, effectiveness test with ground-based measurement, simulated spectral data and MODIS LAI product. The approaches resulted in reasonably good accuracy.