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Monitoring of Vegetation Disturbance and Restoration at the Dumping Sites of the Baorixile Open-Pit Mine Based on the LandTrendr Algorithm

Author

Listed:
  • Junting Guo

    (State Key Laboratory of Water Resource Protection and Utilization in Coal Mining, Beijing 102209, China
    National Institute of Low Carbon and Clean Energy, Beijing 102211, China)

  • Quansheng Li

    (State Key Laboratory of Water Resource Protection and Utilization in Coal Mining, Beijing 102209, China)

  • Huizhen Xie

    (College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China)

  • Jun Li

    (College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China)

  • Linwei Qiao

    (College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China)

  • Chengye Zhang

    (College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China)

  • Guozhu Yang

    (State Grid General Aviation Co., Ltd., Beijing 102209, China)

  • Fei Wang

    (State Key Laboratory of Water Resource Protection and Utilization in Coal Mining, Beijing 102209, China
    National Institute of Low Carbon and Clean Energy, Beijing 102211, China)

Abstract

Overstocked dumping sites associated with open-pit coal mining occupy original vegetation areas and cause damage to the environment. The monitoring of vegetation disturbance and restoration at dumping sites is important for the accurate planning of ecological restoration in mining areas. This paper aimed to monitor and assess vegetation disturbance and restoration in the dumping sites of the Baorixile open-pit mine using the LandTrendr algorithm and remote sensing images. Firstly, based on the temporal datasets of Landsat from 1990 to 2021, the boundaries of the dumping sites in the Baorixile open-pit mine in Hulunbuir city were extracted. Secondly, the LandTrendr algorithm was used to identify the initial time and duration of vegetation disturbance and restoration, while the Normalized Difference Vegetation Index (NDVI) was used as the input parameter for the LandTrendr algorithm. Thirdly, the vegetation restoration effect at the dumping sites was monitored and analyzed from both temporal and spatial perspectives. The results showed that the dumping sites of the Baorixile open-pit mine were disturbed sharply by the mining activities. The North dumping site, the South dumping site, and the East dumping site (hereinafter referred to as the North site, the South site, and the East site) were established in 1999, 2006, and 2010, respectively. The restored areas were mainly concentrated in the South site, the East site, and the northwest of the North site. The average restoration intensity in the North site, South site, and East site was 0.515, 0.489, and 0.451, respectively, and the average disturbance intensity was 0.371, 0.398, and 0.320, respectively. The average restoration intensity in the three dumping sites was greater than the average disturbance intensity. This study demonstrates that the combination of temporal remote sensing images and the LandTrendr algorithm can follow the vegetation restoration process of an open-pit mine clearly and can be used to monitor the progress and quality of ecological restoration projects such as vegetation restoration in mining areas. It provides important data and support for accurate ecological restoration in mining areas.

Suggested Citation

  • Junting Guo & Quansheng Li & Huizhen Xie & Jun Li & Linwei Qiao & Chengye Zhang & Guozhu Yang & Fei Wang, 2022. "Monitoring of Vegetation Disturbance and Restoration at the Dumping Sites of the Baorixile Open-Pit Mine Based on the LandTrendr Algorithm," IJERPH, MDPI, vol. 19(15), pages 1-15, July.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:9066-:d:871409
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    References listed on IDEAS

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    1. Dawuda Usman Kaku & Yonghong Cao & Yousef Ahmed Al-Masnay & Jean Claude Nizeyimana, 2021. "An Integrated Approach to Assess the Environmental Impacts of Large-Scale Gold Mining: The Nzema-Gold Mines in the Ellembelle District of Ghana as a Case Study," IJERPH, MDPI, vol. 18(13), pages 1-20, July.
    2. Chengye Zhang & Huiyu Zheng & Jun Li & Tingting Qin & Junting Guo & Menghao Du, 2022. "A Method for Identifying the Spatial Range of Mining Disturbance Based on Contribution Quantification and Significance Test," IJERPH, MDPI, vol. 19(9), pages 1-21, April.
    3. Lindsey L. Sloat & James S. Gerber & Leah H. Samberg & William K. Smith & Mario Herrero & Laerte G. Ferreira & Cécile M. Godde & Paul C. West, 2018. "Increasing importance of precipitation variability on global livestock grazing lands," Nature Climate Change, Nature, vol. 8(3), pages 214-218, March.
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