Jl. Privette et al., OPTIMAL SAMPLING CONDITIONS FOR ESTIMATING GRASSLAND PARAMETERS VIA REFLECTANCE MODEL INVERSIONS, IEEE transactions on geoscience and remote sensing, 34(1), 1996, pp. 272-284
The sensitivity of grassland bidirectional reflectance to soil, vegeta
tion, irradiance, and sensor parameters is assessed, Based on these re
sults, a vegetation Bidirectional Reflectance Distribution Function (B
RDF) model is inverted with ground reflectance data from the First ISL
SCP Field Experiment (FIFE), Results suggest that leaf area index (LAI
) is most accurately retrieved from data gathered in near-infrared ban
ds at low solar zenith angles (SZA), and leaf angle distribution is be
st retrieved from data gathered in near-infrared bands at high SZA, Ge
nerally, leaf optical properties are more accurately estimated from da
ta acquired at high SZA. Canopy albedo and fraction of absorbed photos
ynthetically active radiation (fAPAR) are also estimated and compared
to measured values, Albedo estimates are accurate to about +/-0.01 (4%
relative) when model parameters are determined from reflectance data
gathered under preferred conditions, Estimates of fAPAR are less accur
ate, These results provide a guide for efficiently sampling surface re
flectance and accurately retrieving parameters for use in climate and
ecosystem models.