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Computer-based classification accuracy due to the spatial resolution using per-point versus per-field classification techniquesData sets simulating three different spatial resolutions (SR's) are computed from data with a 15-m nominal SR that were obtained with NASA's Thermatic Mapper Simulator from an altitude of about 6 km. The classification accuracies (CA's) achieved with the data of each of the four different SR's using a per-point Gaussian maximum likelihood classifier (GMLC) are intercompared. The CA's obtained using simulated 30-m SR data with the per-point GMLC are compared with the CA's achieved with a per-field classifier. It is found that: (1) the use of successively higher SR data resulted in lower overall CA's for classifications with the per-point GMLC, especially in cover classes associated with relatively higher spectral variability across adjacent pixels; (2) higher CA's were achieved using the per-field classifier with 30-m SR data than were achieved with the per-point GMLC; and (3) the largest increases in CA's were achieved with the per-field classifier in cover classes associated with relatively high levels of spectral variability across adjacent pixels.
Document ID
19820063229
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Latty, R. S.
(Technicolor Graphic Services, Inc. Moffet Field, CA, United States)
Hoffer, R. M.
(Purdue University West Lafayette, IN, United States)
Date Acquired
August 10, 2013
Publication Date
January 1, 1981
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: Machine processing of remotely sensed data with special emphasis on range, forest, and wetlands assessment
Location: West Lafayette, IN
Start Date: June 23, 1981
End Date: June 26, 1981
Accession Number
82A46764
Funding Number(s)
CONTRACT_GRANT: NAS9-15889
Distribution Limits
Public
Copyright
Other

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