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Spatiotemporal dynamics of ecological environment quality in arid and sandy regions with a particular remote sensing ecological index: a study of the Beijing-Tianjin Sand source region
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Spatiotemporal dynamics of ecological environment quality in arid and sandy regions with a particular remote sensing ecological index: a study of the Beijing-Tianjin Sand source region
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Spatiotemporal dynamics of ecological environment quality in arid and sandy regions with a particular remote sensing ecological index: a study of the Beijing-Tianjin Sand source region
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Journal Article
Spatiotemporal dynamics of ecological environment quality in arid and sandy regions with a particular remote sensing ecological index: a study of the Beijing-Tianjin Sand source region
2025
Overview
Evaluating Ecological Environment Quality (EEQ) is crucial for sustainable development, particularly in arid and semi-arid regions with particular environmental and socioeconomic characteristics. This study introduces a Particular Remote Sensing Ecological Index (PRSEI), incorporating the Sand Index (SI) and Turbidity Index (TI) based on the traditional Remote Sensing Ecological Index (RSEI), to better reflect the EEQ in the Beijing-Tianjin Sand Source Region (BTSSR) from 2000 to 2020. The Theil-Sen median, Mann–Kendall test, and Hurst index were applied to explore the trend of PRSEI, and the optimal parameters-based geographical detector model evaluated the impact of influencing factors and their interactions. The results in this study indicate that (1) PRSEI and RSEI demonstrated high consistency (R2 = 0.972), with PRSEI outperforming RSEI in capturing regional ecological differences. (2) The EEQ of BTSSR was significantly improved during the study period, and PRSEI showed a strong uptrend in most areas, 61.771% of the areas were strongly improved, 26.154% were light improved, and 11.821% were seriously degraded. The future development trend is mainly based on the “Up-Up” model, which indicates that the EEQ of BTSSR is generally improved. The mean q-value for the single-factor detection was 0.382, while for the interactive detection, it was 0.612, highlighting the significant role of factors’ interaction in PRSEI variation. In general, this study serves as a scientific foundation for advancing ecological conservation and fostering sustainable socio-economic development in arid and semi-arid regions, offering critical insights to support targeted strategies and informed decision-making.
Publisher
Taylor & Francis Group
