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Home / Photogrammetric Engineering & Remote Sensing, Number 3 / March 2012

Open Access Identifying Revegetated Mines as Disturbance/Recovery Trajectories Using an Interannual Landsat Chronosequence

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The objective of this study was to assess whether surface coal mines in the heavily forested southern Appalachian regions of USA can be separated from the other prevalent forest-replacing disturbances through automated analysis of an interannual chronosequence of Landsat Thematic Mapper and Enhanced Thematic Mapper Plus images. Forest replacing disturbances were first identified using a vegetation index (VI) threshold, then classified using descriptors of the disturbance/recovery trajectory: disturbance minimum, recovery slope, and recovery maximum. Three VIs (normalized difference vegetation index or NDVI; the tasseled cap greenness/brightness ratio, TC G/B; and the inverse of Landsat band 3, B3I) were used to analyze multitemporal trajectories generated using both pixels and objects. Classification accuracies using objects were better than those obtained using pixels for all VIs. The highest object-based classification accuracy was achieved using TC G/B (89 percent), followed by NDVI (88 percent) and B3I (80 percent). The diagnostic parameters in mined-land trajectories were found to be distinctly different from other landscape disturbances, leading to a satisfactory classification based on disturbance/recovery trajectories.

Document Type: Research Article

Publication date: 01 March 2012

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  • The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.

    Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies.
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