Optimal sampling conditions for estimating grassland parameters via reflectance

The sensitivity of grassland bidirectional reflectance to soil, vegetation, irradiance, and sensor parameters is assessed. Based on these results, a vegetation bidirectional reflectance distribution function (BRDF) model is inverted with ground reflectance data from the First ISLSCP Field Experiment (FIFE). Results suggest leaf area index (LAI) is most accurately retrieved from data gathered in near-infrared bands at low solar zenith angles (SZA), and leaf angle distribution is best retrieved from data gathered in near-infrared bands at SZA. Generally, leaf optical properties are more accurately estimated from data acquired at high SZA. Canopy albedo and fraction of absorbed photosynthetically active radiation (fAPAR) are also estimated and compared to measured values. Albedo estimates are accurate to about /spl plusmn/0.01 (4% relative) when model parameters are determined from reflectance data gathered under preferred conditions. Estimates of fAPAR are less accurate. These results provide a guide for efficiently sampling surface reflectance and accurately retrieving parameters for use in climate ecosystem models.