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.
References
Bai Y, Wu J, Xing Q, Pan Q, Huang J, Yang D, Han X (2008) Primary production and rain use efficiency across a precipitation gradient on the Mongolia plateau. Ecology 89(8):2140–2153
Bian Z, Inyang HI, Daniels JL, Otto F, Struthers S (2010) Environmental issues from coal mining and their solutions. Min Sci Technol 20(2):215–223
CMEP/CMLR. 2014. The report on the National General Survey of soil contamination. China Ministry of Environmental of Protection and China Ministry of Land Resource
Coops NC, Wulder MA, Iwanicka D (2009) Large area monitoring with a MODIS-based disturbance index (DI) sensitive to annual and seasonal variations. Remote Sens Environ 113(6):1250–1261
Fernandez-Manso A, Quintano C, Roberts D (2012) Evaluation of potential of multiple endmember spectral mixture analysis (MESMA) for surface coal mining affected area mapping in different world forest ecosystems. Remote Sens Environ 127:181–193
John R, Chen J, Kim Y, Ou-yang ZT, Xiao J, Park H, Shao C, Zhang Y, Amarjargal A, Batkhshig O, Qi J (2015) Differentiating anthropogenic modification and precipitation-driven change on vegetation productivity on the Mongolian Plateau. Landscape Ecol 31:547–566
Li A, Wu J, Huang J (2012) Distinguishing between human-induced and climate-driven vegetation changes: a critical application of RESTREND in inner Mongolia. Landscape Ecol 27(7):969–982
Mildrexler DJ, Zhao M, Heinsch FA, Running SW (2007) A new satellite-based methodology for continental-scale disturbance detection. Ecol Appl 17(1):235–250
Mildrexler DJ, Zhao M, Running SW (2009) Testing a MODIS global disturbance index across North America. Remote Sens Environ 113(10):2103–2117
Pickett STA, Wu JG, Cadenasso ML (1999) Patch dynamics and the ecology of disturbed ground. In: Walker LR (ed) Ecosystems of disturbed ground. Ecosystems of the World 16. Elsevier, Amsterdam, pp 707–722
Qian T, Bagan H, Kinoshita T, Yamagata Y (2014) Spatial-temporal analyses of surface coal mining dominated land degradation in Holingol, Inner Mongolia. IEEE J Sel Top Appl Earth Obs Remote Sens 7(5):1675–1687
Qiao J, Yu D, Wu J (2018) How do climatic and management factors affect agricultural ecosystem services? A case study in the agro-pastoral transitional zone of northern China. Sci Total Environ 613:314–323
Sala OE, Gherardi LA, Reichmann L, Jobbagy E, Peters D (2012) Legacies of precipitation fluctuations on primary production: theory and data synthesis. Philos Trans R Soc Lond B 367(1606):3135–3144
Tao S, Fang J, Zhao X, Zhao S, Shen H, Hu H, Tang Z, Wang Z, Guo Q (2015) Rapid loss of lakes on the Mongolian Plateau. Proc Natl Acad Sci 112(7):2281–2286
Waring RH, Coops NC, Running SW (2011) Predicting satellite-derived patterns of large-scale disturbances in forests of the Pacific Northwest Region in response to recent climatic variation. Remote Sens Environ 115(12):3554–3566
Wessels KJ, Prince S, Malherbe J, Small J, Frost P, VanZyl D (2007) Can human-induced land degradation be distinguished from the effects of rainfall variability? A case study in South Africa. J Arid Environ 68(2):271–297
World Coal Institute (2005) The coal resource: a comprehensive overview of coal. https://www.worldcoal.org/sites/default/files/resources_files/coal_resource_overview_of_coal_report%2803_06_2009%29.pdf
Zeng X, Liu Z, He C, Ma Q, Wu J (2018) Quantifying surface coal-mining patterns to promote regional sustainability in Ordos. Inner Mongolia. Sustainability 10(4):1135-1-17
Zhao X, Hu H, Shen H, Zhou D, Zhou L, Myneni RB, Fang J (2015) Satellite-indicated long-term vegetation changes and their drivers on the Mongolian Plateau. Landscape Ecol 30(9):1599–1611
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.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Ma, Q., He, C. & Fang, X. A rapid method for quantifying landscape-scale vegetation disturbances by surface coal mining in arid and semiarid regions. Landscape Ecol 33, 2061–2070 (2018). https://doi.org/10.1007/s10980-018-0726-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10980-018-0726-9