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Himawari-8/AHI is a new geostationary sensor that can observe the land surface with high temporal frequency. Bidirectionalreflectance derived by the Advanced Himawari Imager (AHI) includes information regarding land surface properties such as albedo,vegetation condition, and forest structure. This information can be extracted by modeling bidirectional reflectance using abidirectional reflectance distribution function (BRDF). In this study, a kernel-driven BRDF model was applied to the red and nearinfrared reflectance observed over 8 hours during daytime to express intraday changes in reflectance. We compared the goodness offit for six combinations of model kernels. The Ross-Thin and Ross-Thick kernels were selected as the best volume kernels for the redand near infrared bands, respectively. For the geometric kernel, the Li-sparse-Reciprocal and Li-Dense kernels displayed similargoodness of fit. The coefficient of determination and regression residuals showed a strong dependency on the azimuth angle of landsurface slopes and the time of day that observations were made. Atmospheric correction and model adjustment of the terrain were themain issues encountered. These results will help to improve the BRDF model and to extract surface properties from bidirectionalreflectance

BIDIRECTIONAL REFLECTANCE MODELING OF THE GEOSTATIONARY SENSOR HIMAWARI-8/AHI USING A KERNEL-DRIVEN BRDF MODEL