Objectives The Li-Sparse reciprocal kernel is based on the geometric optical modeling approach developed by Li and Strahler, in which the angular reflectance is the sum of four component signatures weighted by their areal proportions. In the derivation of the simple kernel form used in the MODIS BRDF/Albedo algorithm, there are two main assumptions: 1) the two shadowed components are perfectly dark; and 2) the two sunlit components are equally bright. The main reason for these assumptions was that shadowing is the major effect captured by geometric optical models and the variations within shadowed areas and sunlit areas are less important. However, there are some cases in which these assumptions seem to be invalid, such as sparse shrubs on a bright soil background and sparse evergreens on a snow background. The objective of this work is to assess the performance of MODIS BRDF/Albedo Algorithm in these cases using simulated observations from the Geometric- Optical Radiative-Transfer (GORT) model. Performance of MODIS BRDF/Albedo Algorithm in Dark-Objects-on-Bright-Background Cases Jicheng Liu, Crystal Schaaf, Alan Strahler, Ziti Jiao, Yanmin Shuai, and Qingling Zhang Department of Geography and Center for Remote Sensing, Boston University, Boston, MA 02215, USA Introduction The operational MODIS (MODerate Resolution Imaging Spectroradiometer) BRDF/Albedo product uses registered, multiband, multidate, atmospherically corrected surface reflectance data to best fit BRDF (Bidirectional Reflectance Distribution Function) shapes in seven spectral bands at 500m resolution (Collection 5) on a 16-day cycle (Lucht et al., 2000). In the algorithm, a linear kernel-based semiempirical model, which uses the RossThick kernel for volumetric scattering and LiSparse- Reciprocal kernel for geometric scattering, is used. This algorithm has been validated with regard to its model fitting ability, its performance under sparse angular sampling, and its sensitivity to noise, and its retrievals have been found to be generally reliable (Lucht et al., 2000). Methodology In the GORT model, the forest canopy is characterized as a collection of individual spheroidal tree crowns that cast shadows on other crowns and the background with all four components of a scene (sunlit crown, sunlit background, shadowed crown and shadowed background) fully modeled (Li et al., 1995). It requires canopy geometry parameters as well as spectral parameters of leaves and the background. A number of simulated observations are used to invert the MODIS BRDF/Albedo algorithm for the retrieval, and then a comparison is done between the BRDF shapes from the retrieval and the GORT model. 12m x 12m area. R=1m, Density = 0.5 trees/m 2, b/r=1, h/b=2. Snow background GORT model runs with all those four components considered. Pick up some observations from modeled BRDF. Feed in these observations to MODIS BRDF/Albedo algorithm and do the retrieval. Comparison between BRDF shapes from the GORT model and from MODIS algorithm. Results - 11 observations The comparison shows that, when 11 observations with a solar zenith angle of 30 degrees and view zenith angle ranging from -55 degrees to 55 degrees are used in the inversion, both visible band and near infrared band inversions fitted with the GORT model results very well. However, BRDFs become increasingly different as view zenith angle increases beyond 70 degrees. The algorithm also performs well at large solar zenith angles, such as 60 degrees, which are common in high latitude areas. Results - 7 observations In the MODIS BRDF/Albedo algorithm, a full inversion is performed when the number of observations is greater than or equal to 7. The comparison results also show that, if the view zenith angles are well distributed, the algorithm performs well even when there are only 7 observations available. However, its performance is poor when the seven observations are distributed to one side of nadir. In all cases, the discrepancies between the two results are large for high view zenith angles, greater than 70 degrees. However, this is a known issue for this algorithm in general and this effect does not usually impact the resultant albedo computation since the contribution of these angles is very small in the numerical integration due to their low weights. BRDF shapes from MODIS BRDF/Albedo Algorithm Following are single pixel retrievals in tile H23V02 on julian day of 49 in 2001: CONCLUSIONS The MODIS BRDF/Albedo algorithm performs well in the MODIS view zenith angle range given there are enough number of good observations. When the view zenith angles are well distributed, the algorithm also performs reasonably well even if there are only 7 observations available while if the view zenith angle distribution is bad, one- sided for instance, the algorithm may produce a bad retrieval. References: Li, X., Strahler, A. H., and Woodcock, C. E. (1995) A hybrid geometric optical-radiative transfer approach for modeling albedo and directional reflectance of discontinuous canopies. IEEE Trans. Geos. Remote Sens., 33: Lucht, W., Schaaf, C. B., and Strahler, A. H. (2000) An algorithm for the retrieval of albedo from space using semiempirical BRDF models. IEEE Trans. Geosci. Remote Sens., 38: Strahler, A. H., J.-P. Muller, and MODIS Science Team Members (1999) MODIS BRDF/Albedo Product: Algorithm Theoretical Basis Document. NASA EOS-MODIS Doc., V5.0, pp53.