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Pattern recognition of Landsat data based upon temporal trend analysisThe Delta Classifier defined as an agricultural crop classification scheme employing a temporal trend procedure is applied to more than 100 different Landsat data sets collected during the 1974-1975 growing season throughout the major wheat-producing regions of the United States. The classification approach stresses examination of temporal trends of the Landsat mean vectors of crops in the absence of corresponding ground truth information. It is shown that the resulting classifications compare favorably to ground truth estimates for wheat proportion in those cases where ground truth is available, and that the temporal trend procedure yields estimates of the wheat proportion that are comparable to the best results from maximum likelihood classification with photointerpreter-defined training fields.
Document ID
19780034339
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Engvall, J. L.
(NASA Lyndon B. Johnson Space Center Houston, TX, United States)
Tubbs, J. D.
(NASA Lyndon B. Johnson Space Center Houston, TX, United States)
Holmes, Q. A.
(NASA Johnson Space Center Mission Planning and Analysis Div., Houston, Tex., United States)
Date Acquired
August 9, 2013
Publication Date
January 1, 1977
Publication Information
Publication: Remote Sensing of Environment
Volume: 6
Issue: 4, 19
Subject Category
Earth Resources And Remote Sensing
Accession Number
78A18248
Distribution Limits
Public
Copyright
Other

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