IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i3p325-d756376.html
   My bibliography  Save this article

Comparison of the Vegetation Index of Reclamation Mining Areas Calculated by Multi-Source Remote Sensing Data

Author

Listed:
  • Jiameng Hu

    (School of Land Science and Technology, China University of Geosciences, Beijing 100083, China)

  • Baoying Ye

    (School of Land Science and Technology, China University of Geosciences, Beijing 100083, China
    Key Laboratory of Land Consolidation and Rehabilitation, The Ministry of Natural Resources, Beijing 100035, China)

  • Zhongke Bai

    (School of Land Science and Technology, China University of Geosciences, Beijing 100083, China
    Key Laboratory of Land Consolidation and Rehabilitation, The Ministry of Natural Resources, Beijing 100035, China
    Technology Innovation Center of Ecological Restoration Engineering in Mining Area, The Ministry of Natural Resources, Beijing 100083, China)

  • Jiawei Hui

    (School of Land Science and Technology, China University of Geosciences, Beijing 100083, China)

Abstract

Following vegetation reclamation in mining areas, secondary damage may occur at any time, especially in locations that have been mined for decades or even hundreds of years. Effective monitoring strategies are required to accurately assess plant growth and to detect the ecological effects of reclamation. Single satellite monitoring is often difficult to ensure vegetation monitoring needs, therefore multi-source remote sensing is preferred. Different sensor parameters and variation in spectral bands can lead to differences in the type of data obtained, and subsequently, methods for evaluating these differences are required for simultaneous sensor/band use. In this study, NDVI was selected to characterize the vegetation growth of the Antaibao Open-pit Coal Mine Dump by analyzing the correlation between different types of sensors (Landsat 8, HJ, Sentinel-2) and vegetation greenness in order to facilitate satellites’ replacement and supplement. Results show that: (1) Landsat 8 and Sentinel-2 satellite have a high relevance for monitoring the vegetation, but the correlation between these two sensors and HJ is relatively low, (2) the correlation between NDVI values varied by vegetation type, tree (R = 0.8698) > combined grass, shrub and tree (R = 0.7788) > grass (R = 0.7619) > shrub (R = 0.7282), and (3) the phenomenon of “Low value is high, high value is low” in the NDVI value with HJ satellite monitoring may have been caused by a weak signal strength and low sensitivity of the HJ sensor. Comparing the correlation of multi-source sensors to monitor the vegetation in the mining areas can be helpful to determine the alternative supplement of sensors through conversion formulas, which are helpful in realizing the long-term monitoring of dumps and detecting reclamation response in mining areas.

Suggested Citation

  • Jiameng Hu & Baoying Ye & Zhongke Bai & Jiawei Hui, 2022. "Comparison of the Vegetation Index of Reclamation Mining Areas Calculated by Multi-Source Remote Sensing Data," Land, MDPI, vol. 11(3), pages 1-16, February.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:3:p:325-:d:756376
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/3/325/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/3/325/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sungsu Kim & Thelge Buddika Peiris, 2021. "Meta analysis of regression: a review and new approach with application to linear-circular regression model," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(12), pages 2723-2731, June.
    2. Jiawei Hui & Zhongke Bai & Baoying Ye & Zihao Wang, 2021. "Remote Sensing Monitoring and Evaluation of Vegetation Restoration in Grassland Mining Areas—A Case Study of the Shengli Mining Area in Xilinhot City, China," Land, MDPI, vol. 10(7), pages 1-18, July.
    3. Lin, Boqiang & Liu, Jianghua & Yang, Yingchun, 2012. "Impact of carbon intensity and energy security constraints on China's coal import," Energy Policy, Elsevier, vol. 48(C), pages 137-147.
    4. Li, Sijia & Wang, Jinman & Zhang, Min & Tang, Qian, 2021. "Characterizing and attributing the vegetation coverage changes in North Shanxi coal base of China from 1987 to 2020," Resources Policy, Elsevier, vol. 74(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huang, Guobin & Zhang, Jie & Yu, Jian & Shi, Xunpeng, 2020. "Impact of transportation infrastructure on industrial pollution in Chinese cities: A spatial econometric analysis," Energy Economics, Elsevier, vol. 92(C).
    2. Tang, Erzi & Peng, Chong, 2017. "A macro- and microeconomic analysis of coal production in China," Resources Policy, Elsevier, vol. 51(C), pages 234-242.
    3. Dong, Qichen & Lin, Yongyi & Huang, Jieyu & Chen, Zhongfei, 2020. "Has urbanization accelerated PM2.5 emissions? An empirical analysis with cross-country data," China Economic Review, Elsevier, vol. 59(C).
    4. Yang, Zhihao & Hong, Junjie, 2021. "Trade policy uncertainty and energy intensity: Evidence from Chinese industrial firms," Energy Economics, Elsevier, vol. 103(C).
    5. Hughes, Larry & Ranjan, Ashish, 2013. "Event-related stresses in energy systems and their effects on energy security," Energy, Elsevier, vol. 59(C), pages 413-421.
    6. Yuanjie Deng & Lei Jia & Yajun Guo & Hua Li & Shunbo Yao & Liqi Chu & Weinan Lu & Mengyang Hou & Binbin Mo & Yameng Wang & Haiyu Yang & Tongyue Zhang, 2022. "Evaluation of the Ecological Effects of Ecological Restoration Programs: A Case Study of the Sloping Land Conversion Program on the Loess Plateau, China," IJERPH, MDPI, vol. 19(13), pages 1-20, June.
    7. Yip, Tsz Leung & Wong, Mei Chi, 2015. "The Nicaragua Canal: scenarios of its future roles," Journal of Transport Geography, Elsevier, vol. 43(C), pages 1-13.
    8. Viebahn, Peter & Vallentin, Daniel & Höller, Samuel, 2015. "Prospects of carbon capture and storage (CCS) in China’s power sector – An integrated assessment," Applied Energy, Elsevier, vol. 157(C), pages 229-244.
    9. Yifan Shen & Qi Li & Xiangjun Pei & Renjie Wei & Bingmei Yang & Ningfei Lei & Xiaochao Zhang & Daqiu Yin & Shijun Wang & Qizhong Tao, 2023. "Ecological Restoration of Engineering Slopes in China—A Review," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
    10. Huijie Yan, 2015. "The Integration of Energy, Environment and Health Policies in China: A Review," Working Papers halshs-01247183, HAL.
    11. Ranjan, Ashish & Hughes, Larry, 2014. "Energy security and the diversity of energy flows in an energy system," Energy, Elsevier, vol. 73(C), pages 137-144.
    12. Jiaxin Mi & Huping Hou & Zhifeng Jin & Xiaoyan Yang & Yifei Hua, 2023. "Long-Term Impact of Ground Deformation on Vegetation in an Underground Mining Area: Its Mechanism and Suggestions for Revegetation," Land, MDPI, vol. 12(6), pages 1-18, June.
    13. Zhu, Junpeng & Lin, Boqiang, 2020. "Convergence analysis of city-level energy intensity in China," Energy Policy, Elsevier, vol. 139(C).
    14. Ya Shao & Qinxue Xu & Xi Wei, 2023. "Progress of Mine Land Reclamation and Ecological Restoration Research Based on Bibliometric Analysis," Sustainability, MDPI, vol. 15(13), pages 1-19, July.
    15. Huijuan Zhang & Wenkai Liu & Qingfeng Hu & Xiaodong Huang, 2023. "Multi-Scale Integration and Distribution of Soil Organic Matter Spatial Variation in a Coal–Grain Compound Area," Sustainability, MDPI, vol. 15(4), pages 1-17, February.
    16. Shao, Shuai & Liu, Jianghua & Geng, Yong & Miao, Zhuang & Yang, Yingchun, 2016. "Uncovering driving factors of carbon emissions from China’s mining sector," Applied Energy, Elsevier, vol. 166(C), pages 220-238.
    17. Ming Chang & Shuying Meng & Zifan Zhang & Ruiguo Wang & Chao Yin & Yuxia Zhao & Yi Zhou, 2023. "Analysis of Eco-Environmental Quality and Driving Forces in Opencast Coal Mining Area Based on GWANN Model: A Case Study in Shengli Coalfield, China," Sustainability, MDPI, vol. 15(13), pages 1-20, July.
    18. Friedrichs, Jörg & Inderwildi, Oliver R., 2013. "The carbon curse: Are fuel rich countries doomed to high CO2 intensities?," Energy Policy, Elsevier, vol. 62(C), pages 1356-1365.
    19. Shaobo Liu & Li Liu & Jiang Li & Qingping Zhou & Yifeng Ji & Wenbo Lai & Cui Long, 2022. "Spatiotemporal Variability of Human Disturbance Impacts on Ecosystem Services in Mining Areas," Sustainability, MDPI, vol. 14(13), pages 1-20, June.
    20. Huijie Yan, 2015. "The Integration of Energy, Environment and Health Policies in China: A Review," AMSE Working Papers 1548, Aix-Marseille School of Economics, France, revised 10 Nov 2015.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:11:y:2022:i:3:p:325-:d:756376. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.