| Abstract | Climate change studies require consistent, long time series, surface reflectance data. The characterization of the bidirectional reflectance distribution function (BRDF) is important for normalizing the
solar radiation reflected from the earth's surface. We evaluated four BRDF models to identify the preferred approach to the normalization of multiyear National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (AVHRR)
and SPOT4-VEGETATION (VGT) composite images to a common illumination and viewing geometry. Four models by the following authors were included: Walthall, Roujean, Ross-Li, and a new nonlinear temporal angular model (NTAM). NTAM accounts for hotspot
effects and also responds to seasonal changes in land cover properties (using vegetation indexes as surrogate temporal measures). We compared the performance of the models under different scenarios of coefficient derivation and model application
including model ability to reproduce theoretical BRDF curves, model consistency in single, multiyear, and incomplete sampling schemes, and comparison of AVHRR and LANDSAT Thematic Mapper surface reflectance prior and after BRDF normalization. We
found that in all the tests, NTAM yielded the best fits between the observed and estimated values. NTAM requires eight coefficients and a lengthier iterative procedure to derive the coefficients, but the resulting coefficients are applied to the
entire growing season rather than one temporal window. NTAM also performed well for different sensors (AVHRR, VGT) and geographic areas (Canada, east Asia, southern United States). Our results contradict the often-encountered perception that
semiempirical BRDF models for angular normalization are all similarly effective, and the research on this topic is mature. We also describe a procedure for routine normalization of satellite optical data. For northern ecosystems, the NTAM coeffients
derived from AVHRR and VGT data for Canada are available via ftp://ccrs.nrcan.gc.ca. |