Landscape Changes in the Southern Coalfields of West Virginia: Multi-Level Intensity Analysis and Surface Mining Transitions in the Headwaters of the Coal River from 1976 to 2016

Vincenzo Cribari, Michael P. Strager, Aaron E. Maxwell and Charles Yuill
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Vincenzo Cribari: School of Design and Community Development, Davis College of Agriculture, Natural Resources and Design, West Virginia University, Morgantown, WV 26506, USA
Michael P. Strager: Division of Resource Economics and Management, Davis College of Agriculture, Natural Resources and Design, West Virginia University, Morgantown, WV 26506, USA
Aaron E. Maxwell: Department of Geology and Geography, Eberly College of Arts and Science, West Virginia University, Morgantown, WV 26506, USA
Charles Yuill: School of Design and Community Development, Davis College of Agriculture, Natural Resources and Design, West Virginia University, Morgantown, WV 26506, USA

Land, 2021, vol. 10, issue 7, 1-32

Abstract: This study analyzes land-cover transitions in the headwaters of the Big Coal River in the Central Appalachian Region of the US, from 1976 to 2016, where surface mining was found as the major driver of landscape change. The land-change analysis combined Multi-Level Intensity Analysis for two-time intervals (1976–1996, 1996–2016) with Difference Components, to differentiate suspected misclassification errors from actual changes. Two land cover classifications were obtained with segmentation analysis and machine learning algorithms from historical high-resolution aerial images and ancillary data. Intensity Analysis allowed for the inspection of transitions across five land cover (LC) classes and measure the degree of non-stationarity of land change patterns. Results found surface mining-related classes and their transitions, including the effects of reclamation processes on areas mined before the enactment of the Surface Mining Control and Reclamation Act (SMCRA, 1977). Results included changes in settlement distribution, low vegetation, water bodies, and forest class transitions. The findings can be applied to infer similar land-change processes in the more extensive Appalachian region where Mountain Top Removal (MTR) operations are widespread. The overall method can be used to address similar problems and inform landscape managers with detailed data to support land use alternatives and conservation in regions that experienced intense changes and are characterized by anthropogenic disturbances and novel ecosystems.

Keywords: land cover change; mountain top removal; surface mining reclamation act; high resolution images; historic images; orthomosaic; Landsat; ancillary data; machine learning; geographic object-based image analysis (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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