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Exploring the Driving Factors of Remote Sensing Ecological Index Changes from the Perspective of Geospatial Differentiation: A Case Study of the Weihe River Basin, China

Author

Listed:
  • Kaili Zhang

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China)

  • Rongrong Feng

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China)

  • Zhicheng Zhang

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China)

  • Chun Deng

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China)

  • Hongjuan Zhang

    (Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education, Henan University, Kaifeng 475001, China)

  • Kang Liu

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China
    National Forestry and Grassland Administration Urban Forest Ecosystem Research Station, Xi’an 710127, China)

Abstract

Using the Google Earth Engine (GEE) platform, Moderate-resolution image spectroradiometer (MODIS) data of the Weihe River Basin from 2001 to 2021 were acquired, four ecological indicators, namely, greenness, wetness, heat, and dryness, were extracted, and the remote sensing ecological index (RSEI) was constructed through principal component analysis. In addition, the geographic detectors and a multi-scale geographic weighted regression model (MGWR) were used to identify the main driving factors of RSEI changes and capture the differences in spatial changes from different perspectives using multiple indicators. The results show that (1) the quality of the eco-environment in the Weihe River basin improved as a whole from 2001 to 2021, and the RSEI increased from 0.376 to 0.414. In terms of the RSEI grade, the medium RSEI and high RSEI areas increased significantly and the growth rate increased significantly, reaching 26.42% and 27.70%, respectively. (2) Spatially, the quality of the eco-environment in the Weihe River Basin exhibited a spatial distribution pattern that was high in the south and low in the north, among which the quality of the eco-environment in the Weihe River Basin in northern Shaanxi and northwestern Ningxia and Gansu was relatively low. In addition, during the study period, the RSEI of the Qinling Mountains in the southern part of the Weihe River Basin and the Jinghe River and Luohe River areas improved significantly. The urban area on the Guanzhong Plain in the Weihe River Basin experienced rapid economic growth, and urban expansion led to a significant decrease in the quality of the eco-environment. (3) The eco-environment quality in the Weihe River Basin is the result of the interaction of natural, anthropogenic, and landscape pattern factors. All of the interactions between the influencing factors had a stronger influence than those of the individual factors. There were significant differences between the individual drivers and the spatial variation in RSEI, suggesting that different factors dominate the variation in RSEI in different regions, and zonal management is crucial to achieving sustainable management of RSEI. The study shows that to improve the eco-environment quality of the Weihe River Basin, it is necessary to further strengthen ecological protection projects, reasonably allocate landscape elements, and strengthen the resistance and resilience of the ecosystem.

Suggested Citation

  • Kaili Zhang & Rongrong Feng & Zhicheng Zhang & Chun Deng & Hongjuan Zhang & Kang Liu, 2022. "Exploring the Driving Factors of Remote Sensing Ecological Index Changes from the Perspective of Geospatial Differentiation: A Case Study of the Weihe River Basin, China," IJERPH, MDPI, vol. 19(17), pages 1-25, September.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:17:p:10930-:d:904263
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    1. Long Guo & Chao Xu & Hongqi Wu & Mingjie Shi & Yanmin Fan, 2024. "The Decisive Influence of the Improved Remote Sensing Ecological Index on the Terrestrial Ecosystem in Typical Arid Areas of China," Land, MDPI, vol. 13(12), pages 1-23, December.
    2. Xueman Zuo & Jiazheng Li & Ludan Zhang & Zhilong Wu & Sen Lin & Xisheng Hu, 2023. "Spatio-Temporal Variations in Ecological Quality and Its Response to Topography and Road Network Based on GEE: Taking the Minjiang River Basin as a Case," Land, MDPI, vol. 12(9), pages 1-25, September.

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