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Monitoring and Restoration of Mining-Impacted Ecosystems Using Remote Sensing Technology

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ecological Remote Sensing".

Deadline for manuscript submissions: 28 May 2025 | Viewed by 423

Special Issue Editors

The College of Forestry, Beijing Forestry University, Beijing 100083, China
Interests: complexity theory of spatial network; application of quantitative remote sensing in forestry; carbon use efficiency of forest ecosystem
Special Issues, Collections and Topics in MDPI journals
School of Geography, Beijing Normal University, Beijing 100875, China
Interests: earth observation; vegetation modeling; lidar; remote sensing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Under the background of global climate change and sustainable development, the contradiction between mineral resources exploitation and ecological protection is becoming increasingly prominent, and the traditional mining activities lack corresponding thinking about the problems in the field of ecological environment. The degree of destruction of mine ecological environment is closely related to the intensity of mining activities. Large-scale mining leads to irreversible changes in landform, soil structure, landscape heterogeneity, biodiversity, and so on. It is particularly urgent to combine the concept promotion and technological innovation of mine management and ecological restoration to enhance the function of mine ecosystem.

At present, the development of remote sensing science and technology provides new research ideas for ecological restoration and ecosystem function improvement in mining areas. MODIS, Landsat, Sentinel, GF, and other satellite images, LiDAR and other LIDAR data, and UAV data enable us to monitor and analyze the changes in the structure and function of mining ecosystem from different scales and levels, providing important data support for ecological restoration.

This Special Issue focuses on the functional changes in various ecosystems in mining areas in the process of ecological restoration supported by multi-source remote sensing data. The main research areas include high-precision inversion and mapping of mining ecosystems based on multi-source remote sensing image data; the interaction mechanism of structural characteristics and functions of mining ecosystems in the process of ecological restoration; the evolution law and driving mechanism of mining ecosystem structure and function based on long time series remote sensing data; the application of remote sensing technology such as machine learning and GEE in the research of ecological restoration in mining area.

Articles may explore, but are not limited to, the following topics:

  1. High-precision remote sensing identification of mining area ecological restoration based on machine learning and GEE;
  2. Multi-scale high time resolution mapping of mining ecosystem based on multi-source remote sensing data;
  3. Analysis of the evolution law and driving mechanism of mining ecosystem structure and function based on long time series remote sensing data;
  4. Interaction mechanism of structural characteristics and functions of mining ecosystem in the process of ecological restoration;
  5. Nbs (Nature-based Solution) ecosystem structure and function analysis based on multi-source and multi-scale remote sensing mining area.
  6. Dynamic monitoring and benefit assessment analysis of ecological restoration in mining areas based on multi-source remote sensing data.

Dr. Qiang Yu
Prof. Dr. Huaguo Huang
Dr. Jianbo Qi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multi-source remote sensing data
  • remote sensing technology
  • mining ecosystem
  • ecological restoration
  • ecosystem structure and function

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Published Papers (1 paper)

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Research

24 pages, 14623 KiB  
Article
Vegetation Growth Changes and Their Constraining Effects on Ecosystem Services Under Ecological Restoration in the Shendong Mining Area
by Xufei Zhang, Zhichao Chen, Yiheng Jiao, Yiqiang Cheng, Zhenyao Zhu, Shidong Wang and Hebing Zhang
Remote Sens. 2025, 17(10), 1674; https://doi.org/10.3390/rs17101674 - 9 May 2025
Viewed by 179
Abstract
Under the ecological restoration project, the vegetation in the mining area shows a significant improvement trend. Exploring the causal relationship among the implementation of ecological restoration projects in mining areas, vegetation restoration, and the improvement of ecosystem service functions is of great significance [...] Read more.
Under the ecological restoration project, the vegetation in the mining area shows a significant improvement trend. Exploring the causal relationship among the implementation of ecological restoration projects in mining areas, vegetation restoration, and the improvement of ecosystem service functions is of great significance for the current green development of coal mines. Therefore, in this study, we used the kernel Normalized Vegetation Index (kNDVI) to measure how vegetation growth has changed since ecological restoration projects began. Changes in four major ecosystem service functions, including soil conservation, net primary productivity (NPP), water yield, and habitat quality, were assessed before and after the restoration projects. The relationship between kNDVI and ecosystem services was further discussed by using the constraint line method. The results show the following: (1) Under the implementation of ecological restoration projects from 1994 to 2022, the annual vegetation growth rate in the mining area has progressively risen each year at a rate of 0.0046/a. Spatially speaking, 90.44% of the mining area had a substantial upward trend, indicating clear evidence of vegetation restoration. (2) Under the scientific ecological restoration of the mining areas, the total ecosystem service index increased from 0.41 in 1994 to 0.49 in 2022. The functions of ecosystem services have been enhanced to differing extents. (3) KNDVI’s constraint effect on the four ecosystem services changed dramatically before and after the ecological restoration effort. After the ecological restoration project, kNDVI’s constraint on ecosystem services decreased. (4) After restoration, the threshold value of kNDVI for maximizing the benefits of the four ecosystem services ranges from 0.1 to 0.2, and the constraint on the total ecosystem services reaches the threshold value of 0.225. This study employs more comprehensive data to examine the intricate relationship between environmental change and service function, which is crucial for the scientific management of ecological processes and facilitates the sustainable green development of mining areas. Full article
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