Evaluation of Skylab (EREP) Data for Forest and Rangeland Surveys


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Data products from the Skylab Earth Resources Experiment Package were examined monocularly or stereoscopically using a variety of magnifying interprctation devices. Land use, forest types, physiographic sites, and plant communitics, as well as forest stress, were interpreted and mapped at sites in Georgia, South Dakota, and Colorado. Microdensitometric techniques and computer-assisted data analysis and sampling procedures were developed and tested against ground truth. Results indicate that only Skylab S190B color photographs are good for classification of forest and nonforest land (90 to 95 percent correct). Both visual and microdensitometer techniques can separate range plant communities at the Region level (ECOCLASS system) with over 90 percent accuracy. Only mountain pine beetle infestations more than 26 m (85 ft) long could be detected. In a study near Redding, California, radiance from Skylab S190B and LANDSAT sensors was found linearly correlated with terrain reflectance.




Evaluation of ERTS-1 Data for Forest and Rangeland Surveys


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Tests used data gathered by the first Earth Resources Technology Satellite. Results on sites in Georgia, Colorado, and South Dakota indicated that ERTS enlargements, preferably color, would be useful to forest managers of large ownerships for broad area planning. Forest land was distinguished from nonforest land with 90 to 95 percent accuracy, in both photointerpretation and computer-assisted analysis. Further breakdowns of cover types could not be made with acceptable accuracy by either method. Forest disturbances from natural causes or human activity could be detected with 90 percent accuracy when ERTS imagery was compared with 6-year-old aerial photos. Stress from mountain pine beetle could not be detected; ERTS wavebands are too broad to identify dying foliage.




USDA Forest Service Research Paper PSW.


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Earth Resources


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Technical Note


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Proceedings


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