Dynamic Monitoring and Driving Factors Analysis of Eco-Environmental Quality in the Hindu Kush–Himalaya Region

The Hindu Kush–Himalaya (HKH) region is an essential component of the global ecosystem, playing a crucial role in global climate regulation and ecological balance. This study employed a remote sensing ecological index (RSEI) with Geodetector to evaluate the eco-environmental quality and its driving factors within the HKH region. Results revealed a statistically significant upward trend (p < 0.05) in eco-environmental quality across the HKH region during 2001–2023, with the average RSEI value increasing by 23.9%. Areas classified as the Good/Excellent grades (RSEI > 0.6) expanded by ~12%, while areas at the Very Poor grade (RSEI ≤ 0.2) shrunk by ~20%. However, areas classified as the Poor (0.2 < RSEI ≤ 0.4) and Moderate (0.4 < RSEI ≤ 0.6) grades increased by ~11% and ~5%, respectively. This resulted in ~11% of the total area degraded across the HKH. Spatially, the highest ecological quality occurred in the southern Himalayan countries (sub-region R2), followed by China’s Tibetan Plateau (sub-region R3), while the northwestern HKH region (sub-region R3) exhibited the lowest ecological quality. Notably, the sub-region R3 and eastern sub-region R1 had the most pronounced improvement. Precipitation and land cover type were the dominant driving factors, exhibiting nonlinear enhancement effects in their interactions, whereas topographic factors (e.g., elevation) had limited but stable influences. These findings elucidate the spatiotemporal dynamics of HKH’s eco-environmental quality and underscore the combined effects of climatic and geomorphic factors, offering a scientific basis for targeted conservation and sustainable development strategies.

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Publication Details

Journal
Remote Sensing
Published
2025-06-22
DOI
https://doi.org/10.3390/rs17132141
Citations
3
Primary Topic
Urban Heat Island Mitigation
Type
article
Field-Weighted Citation Impact
2.40

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article

Dynamic Monitoring and Driving Factors Analysis of Eco-Environmental Quality in the Hindu Kush–Himalaya Region

Huijie Yu, Fangmin Zhang, Xiaofei Wang, Zhen Yu et al.
3 citations
Remote Sensing
Urban Heat Island Mitigation
2.40
article

Dynamic Monitoring and Driving Factors Analysis of Eco-Environmental Quality in the Hindu Kush–Himalaya Region

Huijie Yu, Fangmin Zhang, Xiaofei Wang, Zhen Yu, Jinge Yu
article en
3 citations

Abstract

The Hindu Kush–Himalaya (HKH) region is an essential component of the global ecosystem, playing a crucial role in global climate regulation and ecological balance. This study employed a remote sensing ecological index (RSEI) with Geodetector to evaluate the eco-environmental quality and its driving factors within the HKH region. Results revealed a statistically significant upward trend (p < 0.05) in eco-environmental quality across the HKH region during 2001–2023, with the average RSEI value increasing by 23.9%. Areas classified as the Good/Excellent grades (RSEI > 0.6) expanded by ~12%, while areas at the Very Poor grade (RSEI ≤ 0.2) shrunk by ~20%. However, areas classified as the Poor (0.2 < RSEI ≤ 0.4) and Moderate (0.4 < RSEI ≤ 0.6) grades increased by ~11% and ~5%, respectively. This resulted in ~11% of the total area degraded across the HKH. Spatially, the highest ecological quality occurred in the southern Himalayan countries (sub-region R2), followed by China’s Tibetan Plateau (sub-region R3), while the northwestern HKH region (sub-region R3) exhibited the lowest ecological quality. Notably, the sub-region R3 and eastern sub-region R1 had the most pronounced improvement. Precipitation and land cover type were the dominant driving factors, exhibiting nonlinear enhancement effects in their interactions, whereas topographic factors (e.g., elevation) had limited but stable influences. These findings elucidate the spatiotemporal dynamics of HKH’s eco-environmental quality and underscore the combined effects of climatic and geomorphic factors, offering a scientific basis for targeted conservation and sustainable development strategies.

Remote SensingVol. 17(13)
Nanjing University of Information Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 12%
Urban Heat Island Mitigation
2.40
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