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Characterization and classification of South American land cover types using satellite dataVarious methods are compared for carrying out land cover classifications of South America using multitemporal Advanced Very High Resolution Radiometer data. Fifty-two images of the normalized difference vegetation index (NDVI) from a 1-year period are used to generate multitemporal data sets. Three main approaches to land cover classification are considered, namely the use of the principal components transformed images, the use of a characteristic curves procedure based on NDVI values plotted against time, and finally application of the maximum likelihood rule to multitemporal data sets. Comparison of results from training sites indicates that the last approach yields the most accurate results. Despite the reliance on training site figures for performance assessment, the results are nevertheless extremely encouraging, with accuracies for several cover types exceeding 90 per cent.
Document ID
19880027254
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Townshend, J. R. G.
(Maryland Univ. College Park, MD, United States)
Justice, C. O.
(Maryland, University College Park, United States)
Kalb, V.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
August 13, 2013
Publication Date
August 1, 1987
Publication Information
Publication: International Journal of Remote Sensing
Volume: 8
ISSN: 0143-1161
Subject Category
Earth Resources And Remote Sensing
Accession Number
88A14481
Funding Number(s)
CONTRACT_GRANT: NAG5-399
CONTRACT_GRANT: NERC-F60/G6/12
Distribution Limits
Public
Copyright
Other

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