Actions for Land use classification using texture information in ERTS-A MSS imagery

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Land use classification using texture information in ERTS-A MSS imagery

Author
Haralick, R. M.
Published
Jan 1, 1973.
Physical Description
1 electronic document
Additional Creators
Shanmugam, K. S. and Bosley, R.
Online Version

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Unclassified, Unlimited, Publicly available.
Free-to-read Unrestricted online access
Summary
The author has identified the following significant results. Preliminary digital analysis of ERTS-1 MSS imagery reveals that the textural features of the imagery are very useful for land use classification. A procedure for extracting the textural features of ERTS-1 imagery is presented and the results of a land use classification scheme based on the textural features are also presented. The land use classification algorithm using textural features was tested on a 5100 square mile area covered by part of an ERTS-1 MSS band 5 image over the California coastline. The image covering this area was blocked into 648 subimages of size 8.9 square miles each. Based on a color composite of the image set, a total of 7 land use categories were identified. These land use categories are: coastal forest, woodlands, annual grasslands, urban areas, large irrigated fields, small irrigated fields, and water. The automatic classifier was trained to identify the land use categories using only the textural characteristics of the subimages; 75 percent of the subimages were assigned correct identifications. Since texture and spectral features provide completely different kinds of information, a significant increase in identification accuracy will take place when both features are used together.
Other Subject(s)
Collection
NASA Technical Reports Server (NTRS) Collection.
Note
Document ID: 19730011692.
Accession ID: 73N20419.
E73-10461.
TR-2262-1.
NASA-CR-131261.
Terms of Use and Reproduction
No Copyright.
View MARC record | catkey: 15749898