Spatio-temporal evolutionary analysis of surface ecological quality in Pingshuo open-cast mine area, China

被引:4
作者
Liu, Yahong [1 ]
Zhang, Jin [1 ]
机构
[1] Taiyuan Univ Technol, Coll Min Engn, Taiyuan 030024, Peoples R China
基金
英国科研创新办公室;
关键词
Surface ecology; Spatio-temporal analysis; Remote sensing; Open-pit mining area; Remote sensing ecological index (RSEI); VEGETATION DISTURBANCE; SPATIAL CHANGES; MINING AREAS; LAND-USE; ENERGY; TRANSFORMATION; COEFFICIENT; VALIDATION; INDICATORS; GROWTH;
D O I
10.1007/s11356-023-31650-x
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The open-pit mining area is highly affected by human activities, which aggravate soil erosion and disturb surface ecology, bringing many problems and challenges to its environmental management and restoration, which has received widespread attention. The establishment of an objective, timely and quantitative remote sensing monitoring, and evaluation system for the spatio-temporal evolution of the surface ecological environment in the open-pit mining area is of great significance for its environmental protection, management decisions, and sustainable social development. Based on the Google Earth Engine (GEE) platform, this paper uses Landsat images to construct and calculate the remote sensing ecological index (RSEI) of the Pingshuo open-cast mine area (POMA) from 1990 to 2020 and monitor and evaluate its surface ecological environment. Combined with the Theil-Sen median, Mann-Kendall test, and Hurst index, the spatio-temporal process was analyzed. The results showed that the ecological environmental quality of the mining area first decreased and then increased from 1990 to 2020. 1990-2000 was a period of serious ecological degradation, followed by improvement. The overall improvement area reached 87.03%, and the degradation was concentrated in the coal mining area. Between 1990 and 2020, the Hurst index of the mining area was 0.452, indicating that the region has a fragile ecological environment and has difficult maintaining its stability. The global Moran's I mean value of the RSEI of the study area is 0.92, which combined with Moran's scatter plot to indicate that there is a strong positive spatial correlation rather than a random distribution of its ecological environment. During the study period, the impact on the climate of the ecological environmental change of POMA was weak, and human factors such as coal mining, land reclamation, and social construction were the main driving forces for the change in ecological quality. The results of this study reveal the changing trend of surface ecology in the mining area over the past 30 years, which is helpful for understanding its impact mechanism on ecological quality and provides support for the management of the region.
引用
收藏
页码:7312 / 7329
页数:18
相关论文
共 79 条
  • [11] A TM TASSELED CAP EQUIVALENT TRANSFORMATION FOR REFLECTANCE FACTOR DATA
    CRIST, EP
    [J]. REMOTE SENSING OF ENVIRONMENT, 1985, 17 (03) : 301 - 306
  • [12] The mode of the climacogram estimator for a Gaussian Hurst-Kolmogorov process
    Dimitriadis, Panayiotis
    Koutsoyiannis, Demetris
    [J]. JOURNAL OF HYDROINFORMATICS, 2020, 22 (01) : 160 - 169
  • [13] Cloud detection algorithm comparison and validation for operational Landsat data products
    Foga, Steve
    Scaramuzza, Pat L.
    Guo, Song
    Zhu, Zhe
    Dilley, Ronald D., Jr.
    Beckmann, Tim
    Schmidt, Gail L.
    Dwyer, John L.
    Hughes, M. Joseph
    Laue, Brady
    [J]. REMOTE SENSING OF ENVIRONMENT, 2017, 194 : 379 - 390
  • [14] Life cycle-based environmental performance indicator for the coal-to-energy supply chain: A Chinese case application
    Ghadimi, Pezhman
    Wang, Chao
    Azadnia, Amir Hossein
    Lim, Ming K.
    Sutherland, John W.
    [J]. RESOURCES CONSERVATION AND RECYCLING, 2019, 147 : 28 - 38
  • [15] Google Earth Engine: Planetary-scale geospatial analysis for everyone
    Gorelick, Noel
    Hancher, Matt
    Dixon, Mike
    Ilyushchenko, Simon
    Thau, David
    Moore, Rebecca
    [J]. REMOTE SENSING OF ENVIRONMENT, 2017, 202 : 18 - 27
  • [16] Grifth DA, 1987, Spatial autocorrelation. A Primer
  • [17] Detecting Global Vegetation Changes Using Mann-Kendal (MK) Trend Test for 1982-2015 Time Period
    Guo Meng
    Li Jing
    He Hongshi
    Xu Jiawei
    Jin Yinghua
    [J]. CHINESE GEOGRAPHICAL SCIENCE, 2018, 28 (06) : 907 - 919
  • [18] Tracking vegetation degradation and recovery in multiple mining areas in Beijing, China, based on time-series Landsat imagery
    Han, Yue
    Ke, Yinghai
    Zhu, Lijuan
    Feng, Hui
    Zhang, Qun
    Sun, Zhao
    Zhu, Lin
    [J]. GISCIENCE & REMOTE SENSING, 2021, 58 (08) : 1477 - 1496
  • [19] An analysis of 200-year-long changes in a landscape affected by large-scale surface coal mining: History, present and future
    Hendrychova, Marketa
    Kabrna, Martin
    [J]. APPLIED GEOGRAPHY, 2016, 74 : 151 - 159
  • [20] Hoaglin DC, 2000, Understanding robust and exploratory data analysis, P169