Actions for Mapping Land Cover Types in Amazon Basin Using 1km JERS-1 Mosaic

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Mapping Land Cover Types in Amazon Basin Using 1km JERS-1 Mosaic

Author
Podest, Erika
Published
[2000].
Physical Description
1 electronic document
Additional Creators
Nelson, Bruce, Holt, John, and Saatchi, Sassan S.
Online Version

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Summary
In this paper, the 100 meter JERS-1 Amazon mosaic image was used in a new classifier to generate a I km resolution land cover map. The inputs to the classifier were 1 km resolution mean backscatter and seven first order texture measures derived from the 100 m data by using a 10 x 10 independent sampling window. The classification approach included two interdependent stages: 1) a supervised maximum a posteriori Bayesian approach to classify the mean backscatter image into 5 general land cover categories of forest, savannah, inundated, white sand, and anthropogenic vegetation classes, and 2) a texture measure decision rule approach to further discriminate subcategory classes based on taxonomic information and biomass levels. Fourteen classes were successfully separated at 1 km scale. The results were verified by examining the accuracy of the approach by comparison with the IBGE and the AVHRR 1 km resolution land cover maps.
Other Subject(s)
Collection
NASA Technical Reports Server (NTRS) Collection.
Note
Document ID: 20000055582.
Terms of Use and Reproduction
No Copyright.
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