Evaluation of BRDF modeling for statistical classification of remotely sensed images

Patrick F. Valdez; Gregory W. Donohoe; Sheila E. Motomatsu

doi:10.1117/12.258058

13 November 1996 Evaluation of BRDF modeling for statistical classification of remotely sensed images

Patrick F. Valdez, Gregory W. Donohoe, Sheila E. Motomatsu

Proceedings Volume 2819, Imaging Spectrometry II; (1996) https://doi.org/10.1117/12.258058
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

Reflectance characteristics of typical Earth surface materials are strongly dependent on the incident illumination angle of the sun and viewing geometry of the sensor to the scene. This relationship is summarized in the bidirectional reflectance distribution function (BRDF) of the surface material under investigation. The BRDF, defined to be the ratio of reflected radiance to the incident radiant flux density striking a surface, cannot be measured directly in an operational setting. Laboratory measurements of surface BRDF are possible but tend to be tedious and time consuming. Consequently, the BRDF is often specified with models applied to laboratory spectra obtained under ideal and controlled conditions. In this paper, we evaluate the utility of BRDF modeling in statistical classification/discrimination of Earth surface materials by considering the bidirectional reflectance for multiple viewing angle configurations and the resulting separability between classes.

Citation Download Citation

Patrick F. Valdez, Gregory W. Donohoe, and Sheila E. Motomatsu "Evaluation of BRDF modeling for statistical classification of remotely sensed images", Proc. SPIE 2819, Imaging Spectrometry II, (13 November 1996); https://doi.org/10.1117/12.258058

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