Open AccessJournal Article
Forest type mapping with satellite data
A. G. Dodge,E. S. Bryant +1 more
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TL;DR: In this paper, computer classification of data from Landsat, an earth-orbiting satellite, has resulted in measurements and maps of forest types for two New Hampshire counties, and the acreages of hardwood and softwood types and total forested areas compare favorably with Forest Service figures for the same areas.
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Abstract: Computer classification of data from Landsat, an earth-orbiting satellite, has resulted in measurements and maps of forest types for two New Hampshire counties. The acreages of hardwood and softwood types and total forested areas compare favorably with Forest Service figures for the same areas. These techniques have advantages for field application, particularly in states having forest taxation laws based on general productivity.
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Citations
An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks
TL;DR: In this article, a highly automated algorithm called vegetation change tracker (VCT) has been developed for reconstructing recent forest disturbance history using Landsat time series stacks (LTSS).
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Use of a dark object concept and support vector machines to automate forest cover change analysis
Chengquan Huang,Kuan Song,Sunghee Kim,John R. Townshend,Paul Davis,Jeffrey G. Masek,Samuel N. Goward +6 more
TL;DR: The results suggest that images acquired during leaf-off seasons should not be used in forest cover change analysis in areas where deciduous forests exist and the TDA-SVM method should be especially useful for quantifying forest cover changes over large areas.
289
Automated masking of cloud and cloud shadow for forest change analysis using Landsat images
Chengquan Huang,N. Thomas,Samuel N. Goward,Jeffrey G. Masek,Zhiliang Zhu,John R. Townshend,James E. Vogelmann +6 more
TL;DR: This algorithm for automatically flagging clouds and their shadows in Landsat images is developed and concluded that this algorithm is especially suitable for forest change analysis, because the commission and omission errors of the derived masks are not likely to significantly bias change analysis results.
198
Estimation of managed loblolly pine stand age and density with Landsat ETM+ data
TL;DR: In this paper, the authors analyzed the relationship between Landsat ETM+ reflectance values and commercially managed loblolly pine (Pinus taeda L.) stand characteristics in east Texas.
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