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Reconstructing disturbance history for an intensively mined region by time-series analysis of Landsat imagery

  • Jing Li
  • Carl E. Zipper
  • Patricia F. Donovan
  • Randolph H. Wynne
  • Adam J. Oliphant
Article

Abstract

Surface mining disturbances have attracted attention globally due to extensive influence on topography, land use, ecosystems, and human populations in mineral-rich regions. We analyzed a time series of Landsat satellite imagery to produce a 28-year disturbance history for surface coal mining in a segment of eastern USA’s central Appalachian coalfield, southwestern Virginia. The method was developed and applied as a three-step sequence: vegetation index selection, persistent vegetation identification, and mined-land delineation by year of disturbance. The overall classification accuracy and kappa coefficient were 0.9350 and 0.9252, respectively. Most surface coal mines were identified correctly by location and by time of initial disturbance. More than 8 % of southwestern Virginia’s >4000-km2 coalfield area was disturbed by surface coal mining over the 28-year period. Approximately 19.5 % of the Appalachian coalfield surface within the most intensively mined county (Wise County) has been disturbed by mining. Mining disturbances expanded steadily and progressively over the study period. Information generated can be applied to gain further insight concerning mining influences on ecosystems and other essential environmental features.

Keywords

Remote sensing Appalachian coalfield Mining Change detection Trajectory analysis 

Notes

Acknowledgments

We are grateful for support provided by China Scholarship Council. We appreciate Dr. Jie Ren’s help on post-classification process and Dr. Yang Shao’s recommendation on this paper. We also thank the US Geological Survey, USDA Farm Service Agency, and Virginia Department of Mines Minerals and Energy (DMME) for open access to the data. We offer sincere thanks to Daniel Kestner, Virginia DMME, for his advice and assistance to our study efforts.

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jing Li
    • 1
  • Carl E. Zipper
    • 2
  • Patricia F. Donovan
    • 2
  • Randolph H. Wynne
    • 3
  • Adam J. Oliphant
    • 3
  1. 1.China University of Mining and TechnologyBeijingPeople’s Republic of China
  2. 2.Department of Crop and Soil and Environmental SciencesVirginia Polytechnic Institute and State UniversityBlacksburgUSA
  3. 3.Department of Forest Resources and Environmental ConservationVirginia Polytechnic Institute and State UniversityBlacksburgUSA

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