Tempo-Spatial Variation of Vegetation Coverage and Influencing Factors of Large-Scale Mining Areas in Eastern Inner Mongolia, China

Int J Environ Res Public Health. 2019 Dec 19;17(1):47. doi: 10.3390/ijerph17010047.

Abstract

Vegetation in eastern Inner Mongolia grasslands plays an important role in preventing desertification, but mineral exploration has negative effects on the vegetation of these regions. In this study, the changing trend types of vegetation in eastern Inner Mongolia were analyzed using the normalized difference vegetation index (NDVI) time series from the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI 3g dataset from 1982 to 2015. Meanwhile, changing trend and influencing factors of 25 large-scale mining areas before and after mining were explored with the methods of trend line, residual calculation, and correlation analysis. The vegetation coverage towards increasing in eastern Inner Mongolia decreased in the order of Tongliao>Hinggan League>Chifeng>Hulunbuir>Xilingol over the past 34 years. Vegetation showed a decreasing tendency in 40% mining areas, but an increasing tendency in 60% mining areas after mining. Vegetation change in Shengli No. 1 had a significant correlation with precipitation and human activities after mining. Except Shengli No. 1, an obvious correlation was found between vegetation change and precipitation in 45.83% mining areas after mining. Human activities had significant positive effects on vegetation growth in 25% mining areas. Significant negative effects of human activities were found in 8.34% mining areas, causing the vegetation degradation. However, there were 20.83% mining areas with vegetation changes not affected by precipitation and human activities.

Keywords: GIMMS 3g; Grassland vegetation; coal mining; residual analysis; temperature and precipitation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biodiversity*
  • China
  • Conservation of Natural Resources / statistics & numerical data*
  • Ecosystem*
  • Environmental Monitoring / methods*
  • Grassland*
  • Human Activities / statistics & numerical data*
  • Humans
  • Mining*
  • Spatio-Temporal Analysis