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Continental land cover assessment using Landsat MSS dataA statistical procedure to assess level-II continental resources using Landsat MSS digital data is presented. The statistical procedure involves a two-stage cluster sample within a stratified random sample. The utility of this procedure is assessed by using it to estimate the areal extent of the conifer and hardwood resources of the continental U.S. National estimates of conifer and hardwood derived using this sampling procedure were within 3 percent of U.S. Forest Service (USFS) figures. According to the Landsat-based study, 11 percent of the country is conifer forest and 12 percent is hardwood. The corresponding USFS figures are 13 and 15 percent, respectively. Comparison of the MSS classification products and airphotos showed that the conifer cover class was correctly identified 74 percent of the time and hardwood 80 percent of the time. The average classification accuracy countrywide for the four cover types considered (conifer, hardwood, water, and 'other') is 74 percent, and the overall accuracy is 85 percent. The statistical procedure provides a method of incorporating Landsat MSS digital data as a second state for level-II continental resource assessment. Alternate data sources, e.g., satellite and aircraft photographic imagery, may also be used in conjunction with this statistical model.
Document ID
19870044821
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Nelson, Ross
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Case, David
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Horning, Ned
(Science and Applications Research, Inc. Riverdale, MD, United States)
Anderson, Virgil
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Pillai, Sree
(Purdue University West Lafayette, IN, United States)
Date Acquired
August 13, 2013
Publication Date
February 1, 1987
Publication Information
Publication: Remote Sensing of Environment
Volume: 21
ISSN: 0034-4257
Subject Category
Earth Resources And Remote Sensing
Accession Number
87A32095
Distribution Limits
Public
Copyright
Other

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