IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i12p2239-d1548725.html
   My bibliography  Save this article

Long Time-Series Monitoring and Drivers of Eco-Quality in the Upper-Middle Fen River Basin of the Eastern Loess Plateau: An Analysis Based on a Remote Sensing Ecological Index and Google Earth Engine

Author

Listed:
  • Yanan He

    (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, Ministry of Natural Resources, Beijing 100083, China)

  • Juan He

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

  • Hongyu Wang

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

  • Wei Zhou

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

Abstract

Healthy watershed environments are essential for socioeconomic sustainability. The long-term monitoring and assessment of watershed ecological environments provide a timely and accurate understanding of ecosystem dynamics, informing industry and policy adjustments. This study focused on the upper-middle Fen River Basin (UMFRB) in eastern China’s Loess Plateau and analyzed the long-term spatial and temporal characteristics of eco-quality from 2000 to 2023 by calculating a remote sensing ecological index (RSEI) via the Google Earth Engine (GEE) platform. In addition, this study also explored the trends and future consistency of the RSEI, as well as the impacts of natural and anthropogenic factors on RSEI spatial variations. The findings revealed that (1) the average RSEI value increased from 0.51 to 0.57 over the past 24 years, reflecting an overall improvement in eco-quality, although urban centers in the Taiyuan Basin exhibited localized degradation. (2) The Hurst index value was 0.468, indicating anti-consistency, with most regions showing trends of future decline or exhibiting stochastic fluctuations. (3) Elevation, temperature, precipitation, slope, and land use intensity are significantly correlated with ecological quality. Natural factors dominate in densely vegetated regions, whereas socioeconomic factors dominate in populated plains. These results provide valuable guidance for formulating targeted ecological restoration measures, protection policies, and engineering solutions.

Suggested Citation

  • Yanan He & Baoying Ye & Juan He & Hongyu Wang & Wei Zhou, 2024. "Long Time-Series Monitoring and Drivers of Eco-Quality in the Upper-Middle Fen River Basin of the Eastern Loess Plateau: An Analysis Based on a Remote Sensing Ecological Index and Google Earth Engine," Land, MDPI, vol. 13(12), pages 1-21, December.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:12:p:2239-:d:1548725
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/12/2239/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/13/12/2239/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Haoyang Kang & Meichen Fu & Haoran Kang & Lijiao Li & Xu Dong & Sijia Li, 2024. "The Impacts of Urban Population Growth and Shrinkage on the Urban Land Use Efficiency: A Case Study of the Northeastern Region of China," Land, MDPI, vol. 13(9), pages 1-27, September.
    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.

      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:13:y:2024:i:12:p:2239-:d:1548725. 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.