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自然资源遥感  2025, Vol. 37 Issue (6): 182-190    DOI: 10.6046/zrzyyg.2024323
  技术应用 本期目录 | 过刊浏览 | 高级检索 |
基于PSR和时序预测模型的露天煤矿区生态环境质量遥感评价
刘晋宇1(), 胡晋山1(), 康建荣1, 朱益虎2, 王胜利2
1.江苏师范大学地理测绘与城乡规划学院,徐州 221116
2.江苏省地质测绘大队,南京 211102
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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摘要 

针对露天煤矿开采扰动周边生态环境的量化问题,该文以山西省平朔朔南矿区为研究区,基于压力-状态-响应模型(pressure-state-response,PSR)选取7类评价指标,通过组合赋权构建露天煤矿区遥感生态指数(remote sensing ecological index of open-pit coal mining area,OMRSEI),利用相关性分析和对比分析对OMRSEI进行有效性验证,并选用指数平滑法预测了研究区未来2个年份的生态环境演变趋势。结果表明: ①OMRSEI具有显著的空间相关性和有效性,是一种适用于露天煤矿区生态环境评价的遥感指标; ②研究区2013—2023年生态环境质量总体呈上升趋势,其中安太堡露天矿和安家岭露天矿排土场逐步修复,生态环境质量持续改善,东露天矿生态环境质量则呈现先下降后上升的趋势; ③预测结果表明2025—2027年研究区OMRSEI均值持续上升,生态环境质量持续提升。
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刘晋宇
胡晋山
康建荣
朱益虎
王胜利
关键词 ： 生态质量评价,  露天煤矿,  PSR模型,  时序预测,  定量遥感    
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.
Key words： ecological quality assessment    open-pit coal mine    pressure-state-response (PSR) model    time series prediction    quantitative remote sensing
收稿日期: 2024-10-08      出版日期: 2025-12-31
ZTFLH:  TP79  
基金资助:国家自然科学基金项目“山区采动地表时空动态机理与反演研究”(41671395);“山区煤矿开采对地表水资源影响规律研究”(52074133);江苏师范大学研究生科研与实践创新计划项目“露天矿区土地覆盖变化与生态环境演变研究”(2024XKT0193);江苏省地质局科研项目“地质开采致地表损伤遥感监测与碳汇潜力评估关键技术研究”(2025KJ12);江苏省青年科技人才托举工程项目“地质开采区地表损伤多模态遥感智能监测关键技术研究”(JSTJ-2025-321)
通讯作者: 胡晋山(1973-),男,博士,教授,研究方向为GIS与矿区生态环境治理。Email: xzjshu@163.com。
作者简介: 刘晋宇(2000-),男,硕士研究生,研究方向为遥感与矿区生态评价。Email: 2020221573@jsnu.edu.cn。
引用本文:   
刘晋宇, 胡晋山, 康建荣, 朱益虎, 王胜利. 基于PSR和时序预测模型的露天煤矿区生态环境质量遥感评价[J]. 自然资源遥感, 2025, 37(6): 182-190.
LIU Jinyu, HU Jinshan, KANG Jianrong, ZHU Yihu, WANG Shengli. Remote sensing-based assessment of ecological quality in open-pit coal mining areas based on the pressure-state-response and time series prediction models. Remote Sensing for Natural Resources, 2025, 37(6): 182-190.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/zrzyyg.2024323      或      https://www.gtzyyg.com/CN/Y2025/V37/I6/182
Fig.1  研究区概况图
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  生态指标计算方法
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  研究区OMRSEI各指标权重
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  研究区OMRSEI阈值
Fig.2  研究区OMRSEI分级时空分布图
Fig.3  研究区OMRSEI小提琴图
Fig.4  研究区OMRSEI变化弦图
Fig.5  研究区OMRSEI GMI散点图
Fig.6  研究区OMRSEI LISA聚类图
Fig.7  平朔朔南矿区OMRSEI均值预测图
Fig.8  所选指标相关性热力图
Fig.9  平朔朔南矿区2013—2023年遥感影像和生态质量对比图
[1] Xu D L, Li X F, Chen J, et al. Research progress of soil and vegetation restoration technology in open-pit coal mine:A review[J]. Agriculture, 2023, 13(2):226.
doi: 10.3390/agriculture13020226
[2] 李树志, 李学良, 尹大伟. 碳中和背景下煤炭矿山生态修复的几个基本问题[J]. 煤炭科学技术, 2022, 50(1):286-292.
Li S Z, Li X L, Yin D W. Several basic issues of ecological restoration of coal mines under background of carbon neutrality[J]. Coal Science and Technology, 2022, 50(1):286-292.
[3] 张成业, 李军, 雷少刚, 等. 矿区生态环境定量遥感监测研究进展与展望[J]. 金属矿山, 2022(3):1-27.
Zhang C Y, Li J, Lei S G, et al. Progress and prospect of the quantitative remote sensing for monitoring the eco-environment in mi-ning area[J]. Metal Mine, 2022(3):1-27.
[4] 于洋, 陈炳乾, 花奋奋, 等. 矿山地质环境灾变与保护修复研究现状与展望[J]. 金属矿山, 2024(3):1-18.
Yu Y, Chen B Q, Hua F F, et al. Research status and prospect of mining-induced geo-environmental hazards and geological environment protection[J]. Metal Mine, 2024(3):1-18.
[5] Zhang Z, Li G Q, Su X B, et al. Geochemical controls on the enrichment of fluoride in the mine water of the Shendong mining area,China[J]. Chemosphere, 2021,284:131388.
[6] Lian M, Shang L H, Duan Z, et al. LiDAR mapping of atmospheric atomic mercury in the Wanshan area,China[J]. Environmental Pollution, 2018,240:353-358.
[7] Han X Y, Cao T Y, Yan X L. Comprehensive evaluation of ecological environment quality of mining area based on sustainable deve-lopment indicators:A case study of Yanzhou Mining in China[J]. Environment,Development and Sustainability, 2021, 23(5):7581-7605.
doi: 10.1007/s10668-020-00935-3
[8] 孙宏飞, 李永华, 姬艳芳, 等. 湘西汞矿区土壤中重金属的空间分布特征及其生态环境意义[J]. 环境科学, 2009, 30(4):1159-1165.
Sun H F, Li Y H, Ji Y F, et al. Spatial distribution and ecological significance of heavy metals in soils from Chatian mercury mining deposit,western Hunan Province[J]. Environmental Science, 2009, 30(4):1159-1165.
[9] Tian W X, Li Z Y, Liu W, et al. Grey clustering evaluation on regional eco-environmental quality based on normalized index value[J]. Meteorological and Environmental Research, 2011, 2(4):65-71.
[10] Zhuang Q W, Wu S X, Yan Y Y, et al. Monitoring land surface thermal environments under the background of landscape patterns in arid regions:A case study in Aksu River basin[J]. Science of The Total Environment, 2020,710:136336.
[11] 徐占军, 侯湖平, 张绍良, 等. 采矿活动和气候变化对煤矿区生态环境损失的影响[J]. 农业工程学报, 2012, 28(5):232-240.
Xu Z J, Hou H P, Zhang S L, et al. Effects of mining activity and climatic change on ecological losses in coal mining areas[J]. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(5):232-240.
[12] 徐涵秋. 区域生态环境变化的遥感评价指数[J]. 中国环境科学, 2013, 33(5):889-897.
Xu H Q. A remote sensing index for assessment of regional ecological changes[J]. China Environmental Science, 2013, 33(5):889-897.
[13] 秦璐, 陈炳乾, 于洋, 等. 基于遥感生态指数的矿井关闭前后生态环境时空变化规律研究[J]. 金属矿山, 2023(3):242-249.
Qin L, Chen B Q, Yu Y, et al. Study on the spatio-temporal variation regularity of ecological environment before and after mine closure based on remote sensing ecological index[J]. Metal Mine, 2023(3):242-249.
[14] 陈杏闪, 陈宇, 陆慧, 等. 义能矿区景观格局及生态环境时空动态遥感监测[J]. 遥感技术与应用, 2024, 39(2):426-434.
doi: 10.11873/j.issn.1004-0323.2024.2.0426
Chen X S, Chen Y, Lu H, et al. Temporal and spatial dynamic monitoring of landscape pattern and ecological environment in Yineng mining area[J]. Remote Sensing Technology and Application, 2024, 39(2):426-434.
[15] 岳佳乐, 胡晋山, 郦嘉辉, 等. 基于MAGA-PPC模型的胡家河矿区生态环境质量评价[J]. 金属矿山, 2023(4):236-244.
Yue J L, Hu J S, Li J H, et al. Ecological environment quality eva-luation of Hujiahe mining area based on MAGA-PPC[J]. Metal Mine, 2023(4):236-244.
[16] 刘英, 胡霄, 岳辉, 等. 基于时间序列模型的戈壁荒漠露天矿生态环境评价[J]. 煤炭科学技术, 2023, 51(12):125-139.
Liu Y, Hu X, Yue H, et al. Ecological environmental assessment of Gobi desert open-pit mine based on time series model[J]. Coal Science and Technology, 2023, 51(12):125-139.
[17] 钟安亚, 孙娟, 胡春明, 等. 基于RSEI的北京王平煤矿生态环境修复效果评估及预测[J]. 矿业安全与环保, 2023, 50(4):89-96.
Zhong A Y, Sun J, Hu C M, et al. Evaluation and prediction of ecological environment restoration effect of Beijing Wangping Coal Mine based on RSEI[J]. Mining Safety and Environmental Protection, 2023, 50(4):89-96.
[18] 王锦洋, 卢才武, 李发本, 等. 基于PSR和GA-Elman模型的露天矿区生态安全评价研究[J]. 中国矿业, 2020, 29(2):65-71.
Wang J Y, Lu C W, Li F B, et al. Research on ecological security evaluation of open-pit mine area based on PSR and GA-Elman model[J]. China Mining Magazine, 2020, 29(2):65-71.
[19] Nie X R, Hu Z Q, Ruan M Y, et al. Remote-sensing evaluation and temporal and spatial change detection of ecological environment quality in coal-mining areas[J]. Remote Sensing, 2022, 14(2):345.
doi: 10.3390/rs14020345
[20] 吴舒雁, 朱庆林, 武文. 基于PSR模型的大连湾海岸带生态安全评价研究[J/OL]. 海洋湖沼通报, 2024:1-10.(2024-04-01).https://kns.cnki.net/kcms/detail/37.1141.P.20240401.1502.002.html.
Wu S Y, Zhu Q L, Wu W. An evaluation research on ecological security evaluation of Dalian Bay coastal zone based on the Pressure-State-Response model[J/OL]. Transactions of Oceanology and Limnology, 2024:1-10.(2024-04-01).https://kns.cnki.net/kcms/detail/37.1141.P.20240401.1502.002.html.
[21] 冯海英, 冯仲科, 冯海霞. 一种基于差值指数的颗粒物PM2.5浓度反演新方法[J]. 光谱学与光谱分析, 2018, 38(10):3012.
Feng H Y, Feng Z K, Feng H X. One new method of PM2.5 concentration inversion based on difference index[J]. Spectroscopy and Spectral Analysis, 2018, 38(10):3012.
[22] Yi Z Y, Liu M L, Liu X N, et al. Long-term Landsat monitoring of mining subsidence based on spatiotemporal variations in soil moisture:A case study of Shanxi Province,China[J]. International Journal of Applied Earth Observation and Geoinformation, 2021,102:102447.
[23] Alexander C. Normalised difference spectral indices and urban land cover as indicators of land surface temperature (LST)[J]. International Journal of Applied Earth Observation and Geoinformation, 2020,86:102013.
[24] Gorji T, Sertel E, Tanik A. Monitoring soil salinity via remote sen-sing technology under data scarce conditions:A case study from Turkey[J]. Ecological Indicators, 2017,74:384-391.
[25] Wu R M X, Zhang Z W, Yan W J, et al. A comparative analysis of the principal component analysis and entropy weight methods to establish the indexing measurement[J]. PLoS One, 2022, 17(1):e0262261.
[26] 方时姣, 肖权. 中国区域生态福利绩效水平及其空间效应研究[J]. 中国人口·资源与环境, 2019, 29(3):1-10.
Fang S J, Xiao Q. Research on regional ecological well-being performance and spatial effect in China[J]. China Population,Resources and Environment, 2019, 29(3):1-10.
[27] Billah B, King M L, Snyder R D, et al. Exponential smoothing model selection for forecasting[J]. International Journal of Forecasting, 2006, 22(2):239-247.
doi: 10.1016/j.ijforecast.2005.08.002
[28] 朔州市人民政府. 关于印发朔州市“十四五”生态环境保护规划的通知:朔政发[2022]36号[A/OL].(2022-8-26)[2024-6-12].http://szxxgk.shuozhou.gov.cn/zfwj_1/202212/t20221216_420310.shtml.
Shuozhou Municipal People’s Government. Notice on the issuance of the “14th Five-Year Plan” ecological and environmental protection plan of Shuozhou City:Shuo Zheng Fa [2022]No.36[A/OL].(2022-8-26)[2024-6-12].http://szxxgk.shuozhou.gov.cn/zfwj_1/202212/t20221216_420310.shtml.
[29] 张静, 杨丽萍, 贡恩军, 等. 基于谷歌地球引擎和改进型遥感生态指数的西安市生态环境质量动态监测[J]. 生态学报, 2023, 43(5):2114-2127.
Zhang J, Yang L P, Gong E J, et al. Dynamic monitoring of eco-environmental quality in Xi’an based on GEE and adjusted RSEI[J]. Acta Ecologica Sinica, 2023, 43(5):2114-2127.
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