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Coniferous forest classification and inventory using Landsat and digital terrain dataMachine-processing techniques were used in a Forest Classification and Inventory System (FOCIS) procedure to extract and process tonal, textural, and terrain information from registered Landsat multispectral and digital terrain data. Using FOCIS as a basis for stratified sampling, the softwood timber volumes of the Klamath National Forest and Eldorado National Forest were estimated within standard errors of 4.8 and 4.0 percent, respectively. The accuracy of these large-area inventories is comparable to the accuracy yielded by use of conventional timber inventory methods, but, because of automation, the FOCIS inventories are more rapid (9-12 months compared to 2-3 years for conventional manual photointerpretation, map compilation and drafting, field sampling, and data processing) and are less costly.
Document ID
19860038478
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Franklin, J.
(California, University Santa Barbara, United States)
Logan, T. L.
(California Institute of Technology Jet Propulsion Laboratory, Pasadena, United States)
Woodcock, C. E.
(Boston University MA, United States)
Strahler, A. H.
(Hunter College New York, United States)
Date Acquired
August 12, 2013
Publication Date
January 1, 1986
Publication Information
Publication: IEEE Transactions on Geoscience and Remote Sensing
Volume: GE-24
ISSN: 0196-2892
Subject Category
Earth Resources And Remote Sensing
Accession Number
86A23216
Funding Number(s)
CONTRACT_GRANT: NAS7-100
CONTRACT_GRANT: USFS-53-9158-0-6362
CONTRACT_GRANT: NAS9-15509
Distribution Limits
Public
Copyright
Other

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