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The Decisive Influence of the Improved Remote Sensing Ecological Index on the Terrestrial Ecosystem in Typical Arid Areas of China

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  • Long Guo

    (College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China
    Xinjiang Key Laboratory of Soil and Plant Ecological Processes, Urumqi 830052, China)

  • Chao Xu

    (College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China
    Xinjiang Key Laboratory of Soil and Plant Ecological Processes, Urumqi 830052, China)

  • Hongqi Wu

    (College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China
    Xinjiang Key Laboratory of Soil and Plant Ecological Processes, Urumqi 830052, China)

  • Mingjie Shi

    (College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China
    Xinjiang Key Laboratory of Soil and Plant Ecological Processes, Urumqi 830052, China)

  • Yanmin Fan

    (College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China
    Xinjiang Key Laboratory of Soil and Plant Ecological Processes, Urumqi 830052, China)

Abstract

This study aims to assess the spatiotemporal changes in ecological environment quality (EEQ) in arid regions, using Xinjiang as a case study, from 2000 to 2023, with an improved remote sensing ecological index ( IRSEI ). Due to the complex ecology of arid regions, the traditional remote sensing ecological index (RSEI) has limitations in capturing ecological dynamics. To address this, we propose an enhanced IRSEI model that replaces normalization with standardization, improving robustness against outliers. Additionally, the kernel normalized difference vegetation index ( kNDVI ) and normalized difference salinity index ( NDSI ) are integrated to assess saline areas more effectively. The methodology includes time series analysis, spatial distribution analysis, and statistical evaluations using the difference method, coefficient of variation, and the Hurst index. Results show that the IRSEI more accurately reflects ecological dynamics than the RSEI. Temporal analysis reveals stable overall EEQ, with some areas improving. Spatially, the environment is generally better in the north and in mountainous regions than in the south and plains. Statistical evaluations suggest a positive trend in ecological changes, with improved areas surpassing degraded ones. This study contributes to the monitoring, protection, and management of arid region ecosystems, emphasizing the need for high-resolution data and further analysis.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:12:p:2162-:d:1542121
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    References listed on IDEAS

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    1. Ruihao Cui & Jiazheng Han & Zhenqi Hu, 2022. "Assessment of Spatial Temporal Changes of Ecological Environment Quality: A Case Study in Huaibei City, China," Land, MDPI, vol. 11(6), pages 1-19, June.
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    3. Lingda Zhang & Quanhua Hou & Yaqiong Duan & Sanbao Ma, 2024. "Spatial and Temporal Heterogeneity of Eco-Environmental Quality in Yanhe Watershed (China) Using the Remote-Sensing-Based Ecological Index (RSEI)," Land, MDPI, vol. 13(6), pages 1-20, May.
    4. Miyesier Jumai & Alimujiang Kasimu & Hongwu Liang & Lina Tang & Yimuranzi Aizizi & Xueling Zhang, 2023. "A Study on the Spatial and Temporal Variation of Summer Surface Temperature in the Bosten Lake Basin and Its Influencing Factors," Land, MDPI, vol. 12(6), pages 1-18, June.
    5. 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.
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    7. Ming Shi & Fei Lin & Xia Jing & Bingyu Li & Yang Shi & Yimin Hu, 2023. "Ecological Environment Quality Assessment of Arid Areas Based on Improved Remote Sensing Ecological Index—A Case Study of the Loess Plateau," Sustainability, MDPI, vol. 15(18), pages 1-25, September.
    8. Mei Xu & Bing Guo & Rui Zhang, 2024. "A Novel Approach to Detecting the Salinization of the Yellow River Delta Using a Kernel Normalized Difference Vegetation Index and a Feature Space Model," Sustainability, MDPI, vol. 16(6), pages 1-16, March.
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