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Proceedings Paper

Retrieval of BRDF for pure landcover types from MODIS and MISR using an angular unmixing approach
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Paper Abstract

Information about the surface bi-directional reflectance distribution function (BRDF) and albedo is required as a boundary condition for radiative transfer modeling, aerosol retrievals, cloud retrievals, and atmospheric modeling. The typical spatial resolution provided by MODIS and MISR standard surface products (~1km) is insufficient to measure the BRDF of the pure surface types, because most pixels at this scale correspond to mixed classes. We present an approach for the retrieval of the basic surface BRDFs from the observations of MODIS/Terra and MISR using an angular unmixing method. Our analysis is focused on the Atmospheric Radiation Measurement (ARM) Program area in the Southern Great Planes (SGP) region, which is a predominantly agricultural area with a few major crop types. Pure surface classes were identified using high-resolution (30m) Landsat imagery and results of a ground survey. Assuming that the reflectance for each coarse pixel is a linear superposition of reflectances of basic surface types, it is possible to estimate the original BRDF parameters for each landcover type. In our case, three dominant classes were selected: wheat, grass, and baresoil. In the case of wheat and grass, the dispersion of the results is smaller than in the case of soil. This can be explained by the relatively low fractional coverage of the soil class within large pixels and by the significant variability of soil reflectance depending on wetness, soil type (sand, clay, etc.), and other factors. The correlation between the BRDF shape factors and the normalized difference vegetation index (NDVI) has also been analyzed. There is a high degree of correlation between the NDVI and BRDF isotropic factor (r0 in the case of MISR), while the correlation with other BRDF parameters was found to be smaller. In general, the NDVI can be used as a crude proxy for the BRDF shape.

Paper Details

Date Published: 15 September 2004
PDF: 9 pages
Proc. SPIE 5549, Weather and Environmental Satellites, (15 September 2004); doi: 10.1117/12.559732
Show Author Affiliations
Alexander P. Trishchenko, Canada Ctr. for Remote Sensing (Canada)
Konstantin Khlopenkov, Canada Ctr. for Remote Sensing (Canada)
Yi Luo, Noetix Research Inc. (Canada)

Published in SPIE Proceedings Vol. 5549:
Weather and Environmental Satellites
Thomas H. Vonder Haar; Hung-Lung Allen Huang, Editor(s)

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