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Utility of BRDF Models for Estimating Optimal View Angles in Classification of Remotely Sensed ImagesStatistical classification of remotely sensed images attempts to discriminate between surface cover types on the basis of the spectral response recorded by a sensor. It is well known that surfaces reflect incident radiation as a function of wavelength producing a spectral signature specific to the material under investigation. Multispectral and hyperspectral sensors sample the spectral response over tens and even hundreds of wavelength bands to capture the variation of spectral response with wavelength. Classification algorithms then exploit these differences in spectral response to distinguish between materials of interest. Sensors of this type, however, collect detailed spectral information from one direction (usually nadir); consequently, do not consider the directional nature of reflectance potentially detectable at different sensor view angles. Improvements in sensor technology have resulted in remote sensing platforms capable of detecting reflected energy across wavelengths (spectral signatures) and from multiple view angles (angular signatures) in the fore and aft directions. Sensors of this type include: the moderate resolution imaging spectroradiometer (MODIS), the multiangle imaging spectroradiometer (MISR), and the airborne solid-state array spectroradiometer (ASAS). A goal of this paper, then, is to explore the utility of Bidirectional Reflectance Distribution Function (BRDF) models in the selection of optimal view angles for the classification of remotely sensed images by employing a strategy of searching for the maximum difference between surface BRDFs. After a brief discussion of directional reflect ante in Section 2, attention is directed to the Beard-Maxwell BRDF model and its use in predicting the bidirectional reflectance of a surface. The selection of optimal viewing angles is addressed in Section 3, followed by conclusions and future work in Section 4.
Document ID
20010000488
Acquisition Source
Headquarters
Document Type
Conference Paper
Authors
Valdez, P. F.
(New Mexico Univ. Albuquerque, NM United States)
Donohoe, G. W.
(New Mexico Univ. Albuquerque, NM United States)
Date Acquired
August 20, 2013
Publication Date
February 1, 1997
Publication Information
Publication: NASA University Research Centers Technical Advances in Education, Aeronautics, Space, Autonomy, Earth and Environment
Volume: 1
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
URC97129
Funding Number(s)
CONTRACT_GRANT: NCCW-87
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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