This paper presents a review of the application of Bi-directional Reflectance Distribution Function (BRDF) models in the inference of land surface parameters at regional and global scales using remotely sensed data. Information on land surface parameters, such as Leaf Area Index (LAI), fraction of Absorbed Photosynthetically Active Radiation (fAPAR), aerodynamic surface roughness and albedo, are valuable for understanding the transfer of energy and mass between terrestrial ecosystems and the atmosphere (e.g., carbon, nitrogen and methane cycling) and for ingestion into the lower boundary condition of global circulation models (GCM)s. Conventional techniques for acquiring information on land surface parameters do not account for or utilize the directional nature of surface reflectance. This paper reviews empirical, semi-empirical and, to a lesser extent, physical BRDF models that describe the surface BRDF. In each case examples are given of their application in inferring land surface parameters. The review concludes by discussing the future prospects of BRDF modelling using spaceborne sensors.
IMPACT OF CHANGES IN LAND SURFACE PARAMETERS ON PRECIPITATION OVER INDOCHINA USING A GCM
