| Abstract | The Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA polar orbiting satellites has provided continuous global measurements at fairly high resolution for more than a decade. AVHRR data
have been used successfully in monitoring the weather and environment of our planet. AVHRR channels 1 and 2 measure the visible (0.58-0.68 µm) and near infrared (0.72-1.10 µm) reflected radiances, respectively, that are often employed for remote
sensing of the terrestrial surfaces. However, these measurements are affected significantly by sun-target-sensor geometry due to the bidirectional dependency of the reflected radiances. This study first examines the effects of land cover type,
green biomass, and solar zenith angle (SZA) on the bidirectional reflectance distributions (BRDs) of the visible and near-infrared AVHRR data from NOAA-11 over terrestrial surfaces, and then corrects for these effects by developing some BRD functions
(BRDF). Four land cover types are studied: barren, grassland, forest and cropland. The data used consist of 1-km daily AVHRR measurements for three growing seasons collected over 19 homogeneous land sites (20 x 20 km2 for each site) in the
conterminous United States and parts of Canada. BRD is found to land cover specific and altered significantly by the green biomass present which can be represented by the normalized difference vegetation index (NDVI). The effects of SZA on BRDs are
also observed over all surface types under investigation. Semi-empirical BRDFs were developed to account for these effects that are the functions of the SZA, satellite viewing Zenith angle, relative azimuth angle, and NDVI. Good agreements were found
between the observed and modeled bidirectional dependencies for wide ranges of NDVI and SZA. A single BRDF appears to be sufficient for bidirectional correction of the clear-sky AVHRR measurements make over a specific land cover type throughout a
season. Finally, the developed BRDFs were used to normalize AVHRR reflectance data to a common geometry and to infer the hemispherical albedos for monitoring the seasonal variations of land surfaces. |