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Monitoring and Evaluation of Ecological Environment Quality in the Tianshan Mountains of China Using Remote Sensing from 2001 to 2020

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  • Yuting Liu

    (School of Life and Geography, Kashi University, Kashi 844000, China
    Key Laboratory of Biological Resources and Ecology of Pamirs Plateau in Xinjiang Uygur Autonomous Region, Kashi 844000, China)

  • Chunmei Chai

    (School of Life and Geography, Kashi University, Kashi 844000, China)

  • Qifei Zhang

    (School of Geographical Sciences, Shanxi Normal University, Taiyuan 030031, China)

  • Xinyao Huang

    (School of Life and Geography, Kashi University, Kashi 844000, China)

  • Haotian He

    (School of Life and Geography, Kashi University, Kashi 844000, China)

Abstract

High-altitude mountainous regions are highly vulnerable to climate and environmental shifts, with the current global climate change exerting a profound influence on the ecological landscape of the Tianshan Mountains in China. This study assesses the ecological security quality in the Tianshan Mountains of China from 2001 to 2020 by employing various remote sensing techniques such as the Remote Sensing Ecological Index (RSEI) for evaluation, Normalized Difference Vegetation Index (NDVI) for fractional vegetation cover (FVC) analysis, the CASA model for estimating vegetation primary productivity (NPP), and a carbon source/sink model for calculating the net ecosystem productivity (NEP) of vegetation. The research also delves into the evolutionary trends and impact mechanisms on the ecological environment using land use and meteorological data. The findings reveal that the RSEI’s principal component (PC1) exhibits significant explanatory power, showing a notable increase of 5.90% from 2001 to 2020. Despite relatively stable changes in the RSEI over the past two decades covering 61.37% of the study area, there is a prevalent anti-persistence pattern at 72.39%. Notably, NDVI, FVC, and NPP display upward trends in vegetation characteristics. While most areas in the Tianshan Mountains continue to emit carbon, there is a marked increase in NEP, signifying an enhanced carbon absorption capacity. The partial correlation coefficients between the RSEI and temperature, as well as precipitation, demonstrate statistically significant relationships ( p < 0.05), encompassing 6.36% and 1.55% of the study area, respectively. Temperature displays a predominantly negative correlation in 98.71% of the significantly correlated zones, while precipitation exhibits a prevalent positive correlation. An in-depth analysis of how climate change affects the quality of the ecological environment provides crucial insights for strategic interventions to enhance regional environmental protection and promote ecological sustainability.

Suggested Citation

  • Yuting Liu & Chunmei Chai & Qifei Zhang & Xinyao Huang & Haotian He, 2025. "Monitoring and Evaluation of Ecological Environment Quality in the Tianshan Mountains of China Using Remote Sensing from 2001 to 2020," Sustainability, MDPI, vol. 17(4), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:4:p:1673-:d:1593303
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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.
    2. 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.
    3. Gulbakram Ahmed & Mei Zan & Pariha Helili & Alimujiang Kasimu, 2023. "Responses of Vegetation Phenology to Urbanisation and Natural Factors along an Urban-Rural Gradient: A Case Study of an Urban Agglomeration on the Northern Slope of the Tianshan Mountains," Land, MDPI, vol. 12(5), pages 1-18, May.
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