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Evaluation of Ecological Carrying Capacity and Identification of Its Influencing Factors Based on Remote Sensing and Geographic Information System: A Case Study of the Yellow River Basin in Shaanxi

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  • Zhiyuan Zhu

    (College of Agronomy, Northwest A & F University, Xianyang 712100, China
    The Research Center of Recycle Agricultural Engineering and Technology of Shaanxi Province, Xianyang 712100, China)

  • Zhikun Mei

    (College of Agronomy, Northwest A & F University, Xianyang 712100, China
    The Research Center of Recycle Agricultural Engineering and Technology of Shaanxi Province, Xianyang 712100, China)

  • Shilin Li

    (College of Agronomy, Northwest A & F University, Xianyang 712100, China
    The Research Center of Recycle Agricultural Engineering and Technology of Shaanxi Province, Xianyang 712100, China)

  • Guangxin Ren

    (College of Agronomy, Northwest A & F University, Xianyang 712100, China
    The Research Center of Recycle Agricultural Engineering and Technology of Shaanxi Province, Xianyang 712100, China)

  • Yongzhong Feng

    (College of Agronomy, Northwest A & F University, Xianyang 712100, China
    The Research Center of Recycle Agricultural Engineering and Technology of Shaanxi Province, Xianyang 712100, China)

Abstract

Ecological carrying capacity (ECC), which requires simple scientific evaluation methods, is an important evaluation index for assessing the sustainability of ecosystems. We integrate an innovative research method. Geographic information systems (GIS) and remote sensing (RS) were used to evaluate the ECC of the Yellow River Basin in Shaanxi (YRBS) and to identify the underlying factors that influence it. A calculation method that combines RS and GIS data to estimate ECC based on net primary productivity (NPP) was established. The Carnegie–Ames–Stanford approach model was applied to estimate NPP. The NPP of each land type was used as an indicator to determine the yield factors. The ECC of the watershed was calculated with the carrying capacities of each land-use type. The geographical detector model was used to study the influencing factors of ECC, which provides a scientific basis for the formulation of ecological management policies in YRBS. The results show that from 2000 to 2010, it first decreased by 45.46%, and then increased by 37.06% in 2020, an overall decrease of 13.49 × 10 5 wha in 20 years. Precipitation is the dominant factor that affects ECC, while the impact of human activities on ECC was significantly enhanced during the study period. The developed method based on RS data serves as a reference for ecological evaluation in other similar regions.

Suggested Citation

  • Zhiyuan Zhu & Zhikun Mei & Shilin Li & Guangxin Ren & Yongzhong Feng, 2022. "Evaluation of Ecological Carrying Capacity and Identification of Its Influencing Factors Based on Remote Sensing and Geographic Information System: A Case Study of the Yellow River Basin in Shaanxi," Land, MDPI, vol. 11(7), pages 1-17, July.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:7:p:1080-:d:862831
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    1. Zhenggen Fan & Ji Liu & Hu Yu & Hua Lu & Puwei Zhang, 2022. "Spatial-Temporal Pattern and Influencing Factors of Land Ecological Carrying Capacity in The National Pilot Zones for Ecological Conservation in China," Land, MDPI, vol. 11(12), pages 1-17, December.

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