The Synergistic Effect of Topographic Factors and Vegetation Indices on the Underground Coal Mine Utilizing Unmanned Aerial Vehicle Remote Sensing

Quansheng Li; Feiyue Li; Junting Guo; Li Guo; Shanshan Wang; Yaping Zhang; Mengyuan Li; Chengye Zhang

doi:10.3390/ijerph20043759

The Synergistic Effect of Topographic Factors and Vegetation Indices on the Underground Coal Mine Utilizing Unmanned Aerial Vehicle Remote Sensing

Int J Environ Res Public Health. 2023 Feb 20;20(4):3759. doi: 10.3390/ijerph20043759.

Authors

Quansheng Li^{1

2}, Feiyue Li³, Junting Guo^{1

2}, Li Guo³, Shanshan Wang⁴, Yaping Zhang³, Mengyuan Li³, Chengye Zhang³

Affiliations

¹ State Key Laboratory of Water Resource Protection and Utilization in Coal Mining, CHN Energy Shendong Coal Group Co., Ltd., Ordos 017209, China.
² Department of Ecological Restoration, National Institute of Clean-and-Low-Carbon Energy, Beijing 102211, China.
³ College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China.
⁴ Geological Hazard Investigation and Monitoring Center, China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China.

Abstract

Understanding the synergistic effect between topography and vegetation in the underground coal mine is of great significance for the ecological restoration and sustainable development of mining areas. This paper took advantage of unmanned aerial vehicle (UAV) remote sensing to obtain high-precision topographic factors (i.e., digital elevation model (DEM), slope, and aspect) in the Shangwan Coal Mine. Then, a normalized difference vegetation index (NDVI) was calculated utilizing Landsat images from 2017 to 2021, and the NDVI with the same spatial resolution as the slope and aspect was acquired by down-sampling. Finally, the synergistic effect of topography and vegetation in the underground mining area was revealed by dividing the topography obtained using high-precision data into 21 types. The results show that: (1) the vegetation cover was dominated by "slightly low-VC", "medium-VC", and "slightly high-VC" in the study area, and there was a positive correlation between the slope and NDVI when the slope was more than 5°. (2) When the slope was slight, the aspect had less influence on the vegetation growth. When the slope was larger, the influence of the aspect increased in the study area. (3) "Rapidly steep-semi-sunny slope" was the most suitable combination for the vegetation growth in the study area. This paper revealed the relationship between the topography and vegetation. In addition, it provided a scientific and effective foundation for decision-making of ecological restoration in the underground coal mine.

Keywords: UAV remote sensing; aspect; normalized difference vegetation index; slope; underground coal mine.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Coal
Mining
Remote Sensing Technology*
Unmanned Aerial Devices*

Substances

Coal

Grants and funding

This research was funded by the Open Fund of the State Key Laboratory of Water Resource Protection and Utilization in Coal Mining (Grant number GJNY-20-113-14), National Natural Science Foundation of China (Grant number 42271480, 41901291), and Fundamental Research Funds for the Central Universities (Grant number 2022JCCXDC04, 2022YQDC08).