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Remote Sensing for Natural Resources    2025, Vol. 37 Issue (6) : 182-190     DOI: 10.6046/zrzyyg.2024323
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Remote sensing-based assessment of ecological quality in open-pit coal mining areas based on the pressure-state-response and time series prediction models
LIU Jinyu1(), HU Jinshan1(), KANG Jianrong1, ZHU Yihu2, WANG Shengli2
1. School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China
2. Jiangsu Geologic Surveying and Mapping Institute, Nanjing 211102, China
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Abstract  

To quantify the mining disturbance of open-pit coal mines to surrounding ecosystems, this study investigated the Pingshuo mining area in Shanxi Province. Based on the pressure-state-response (PSR) model, seven types of assessment indicators were selected to construct the remote sensing ecological index of open-pit coal mining area (OMRSEI) through combination weighting. The validity of the OMRSEI was verified through correlation and comparative analyses. Moreover, the trend of ecological evolution in the study area for the next two years was predicted using the exponential smoothing method. The results indicate that the OMRSEI exhibited significant spatial correlation and validity, establishing it as an effective remote sensing indicator for ecological assessment in open-pit coal mining areas. The study area manifested an overall enhanced ecological quality from 2013 to 2023. Specifically, the Antaibao and Anjialing open-pit coal mines witnessed continuously improved ecological quality due to the progressive restoration of waste dumps. In contrast, the Dong open-pit coal mine displayed an ecological quality trend characterized by a first decline and then recovery. The average OMRSEI of the study area is predicted to continuously rise from 2025 to 2027, indicating sustained enhancement in ecological quality.
Keywords ecological quality assessment      open-pit coal mine      pressure-state-response (PSR) model      time series prediction      quantitative remote sensing     
ZTFLH:  TP79  
Issue Date: 31 December 2025
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Jinyu LIU
Jinshan HU
Jianrong KANG
Yihu ZHU
Shengli WANG
Cite this article:   
Jinyu LIU,Jinshan HU,Jianrong KANG, et al. Remote sensing-based assessment of ecological quality in open-pit coal mining areas based on the pressure-state-response and time series prediction models[J]. Remote Sensing for Natural Resources, 2025, 37(6): 182-190.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2024323     OR     https://www.gtzyyg.com/EN/Y2025/V37/I6/182
Fig.1  Overview map of the research area
一级
指标		 二级
指标		 效应① 计算公式
压力 DI - DI=R-N
NDBSI - SI1=$\frac{({S}_{1}+R)-(B+N)}{({S}_{1}+R)+(B+N)}$
IBI=$\frac{2{S}_{1}/({S}_{1}+N)-[N/(N+R)+G/(G+{S}_{1}\left)\right]}{2{S}_{1}/({S}_{1}+N)+[N/(N+R)+G/(G+{S}_{1}\left)\right]}$
NDBSI=(SI+IBI)/2
状态 VHI + NDSVI=(S1-R)/(S1+R)
NRI=N/G
NDVI=(N-R)/(N+R)
VHI=PC1(NDVI,NDSVI,NRI)
SMMI + SMMI=$\sqrt[　]{(N+{S}_{1})/2}$
响应 LST - L=gain×DN+bias
T=K2/ln(K1/L+1)
LST=T/[1+(λT/ρ)ln ε]-273.15
WET + WET=0.151 1B+0.197 3G+0.328 3R+
0.340 7N-0.711 7S1-0.455 9S2
SI2 - SI2=$\sqrt[　]{B\times R}$
Tab.1  Method for calculating ecological indicators
一级指标 二级指标 熵权法权重 层次分析
法权重		 组合权重
压力 DI 0.089 2 0.187 5 0.138 4
NDBSI 0.074 0 0.250 0 0.162 0
状态 VHI 0.734 7 0.187 5 0.461 1
SMMI 0.021 9 0.125 0 0.073 5
响应 LST 0.045 8 0.125 0 0.085 4
WET 0.016 4 0.062 5 0.039 5
SI2 0.017 9 0.062 5 0.040 2
Tab.2  The weights of each index of OMRSEI in the research area
研究年份 阈值1 阈值2 阈值3
2013年 0.400 1 0.475 0 0.540 8
2015年 0.433 0 0.529 5 0.577 8
2017年 0.481 0 0.581 2 0.631 2
2019年 0.431 5 0.518 6 0.562 1
2021年 0.454 8 0.537 4 0.596 4
2023年 0.461 3 0.546 8 0.599 9
均值 0.443 6 0.531 4 0.584 7
Tab.3  OMRSEI thresholds of the research area
Fig.2  Spatial and temporal distribution map of OMRSEI in the research area
Fig.3  Violin plot of OMRSE in the research area
Fig.4  Chord diagram of OMRSEI variation in the research area
Fig.5  GMI I scatter plot of OMRSEI in the research area
Fig.6  LISA cluster map of OMRSEI in the research area
Fig.7  Average prediction map of the OMRSEI in Pingshuo Shuonan mining area
Fig.8  Correlation heatmap of selected indicators
Fig.9  Comparison of remote sensing imagery and ecological quality in Pingshuo Shuonan mining area during 2013—2023
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