LARS Technical Report 062879. Reprint from the Proceedings of the 1979 Symposium on Machine Processing of Remotely Sensed Data, Purdue University, West Lafayette, Indiana, pp. 377-390. This research was supported by NASA Contract NAS 9-15508.


In forestry, as in many other disciplines involving land management, there exists a definite need for timely, reliable information on which to base resource management decisions. This was emphasized in 1974 through the Forest and Rangeland Renewable Resources Planning Act in which the U.S. Congress mandated the U.S. Forest Service to provide information on the condition and productivity of approximately 1.6 billion acres of land, every 10 years. The synoptic view that can be obtained through data from spacecraft altitudes is proving to be of considerable value in developing resource bases, particularly where information over extensive geographic areas is needed. The launch of Landsat-1 in 1972 initiated a new era for land managers by proving that high-quality data can be obtained from satellites at reasonably frequent intervals for nearly any portion of the earth's surface. However, the ability to collect data from satellites far surpasses existing capabilities to analyze and interpret the data in a timely, reliable manner. If computer-aided analysis techniques are to be effectively utilized in conjunction with MSS satellite data on a routine, operational basis, it is important to define and develop the most effective analysis techniques and to determine the level of detail and the reliability of information that can be obtained with such techniques.

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