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Landscape Ecology

, Volume 33, Issue 12, pp 2061–2070 | Cite as

A rapid method for quantifying landscape-scale vegetation disturbances by surface coal mining in arid and semiarid regions

  • Qun Ma
  • Chunyang HeEmail author
  • Xuening Fang
Short Communication
  • 300 Downloads

Abstract

Context

Quantifying landscape-scale vegetation disturbances by surface coal mining (SCM) is crucial for assessing and mitigating its negative impacts on the environment. Methods for detecting such disturbances in woody ecosystems exist, but these methods do not work well for deserts and grasslands in arid and semiarid regions because of their sensitive responses to precipitation variations.

Objectives

The objective of this study was to develop a new index to reliably detect the locations and spatial extents of SCM-induced vegetation disturbances in dryland regions in the face of fluctuating precipitation.

Methods

We have developed a vegetation disturbance index (VDI) that combines MODIS EVI data with precipitation data to detect vegetation disturbances by SCM on the Mongolian Plateau during 2000–2015. The VDI is computed by comparing vegetation production per unit precipitation for a given year with a multi-year mean, and by considering distances from coal-mining areas.

Results

Our results show that the VDI was able to adequately distinguish vegetation disturbances by SCM from climate-driven vegetation changes in five selected sites across the Mongolian Plateau.

Conclusions

The VDI provides an effective tool for quantifying the locations, spatial extents, and severity of vegetation disturbances by SCM in arid and semiarid regions.

Keywords

Vegetation disturbance Surface coal mining MODIS EVI Precipitation Mongolian Plateau 

Notes

Acknowledgements

We are grateful to the anonymous reviewers for their valuable comments on the manuscript of this paper. We also thank Prof. Jianguo Wu for his assistance with conceiving the research idea and revising the manuscript. This research was supported in part by the National Natural Science Foundation of China (Grant Nos. 31700406 & 41621061). It was also supported by Fundamental Research Funds for the Central Universities and the project from the State Key Laboratory of Earth Surface Processes and Resource Ecology, China.

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Center for Human–Environment System Sustainability (CHESS), State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Faculty of Geographical ScienceBeijing Normal UniversityBeijingChina

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