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Remote Sensing
Volume 18
Issue 16
10.3390/rs18162723
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Article

Integrating Multi-Source Remote Sensing and Geospatial Data for Snow Disaster Risk Assessment in Northwestern China

by
Wenxin He
1,2,
Xiaohua Hao
2,3,*,
Fenggui Liu
1,
Donghang Shao
2,3,
Weiguo Wang
4,
Jing Zhao
5,
Yan Liu
6,
Qian Yang
7,
Jian Wang
4 and
Tao Che
2,3
1
School of Geography, Qinghai Normal University, Xining 810008, China
2
Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
3
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
4
College of Geographical Sciences, Shanxi Normal University, Taiyuan 030031, China
5
Xinjiang Transportation Science Research Institute Co., Ltd., Urumqi 830000, China
6
Institute of Desert Meteorology, China Meteorological Administration, Urumgi 830002, China
7
State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2026, 18(16), 2723; https://doi.org/10.3390/rs18162723
Submission received: 9 June 2026 / Revised: 11 July 2026 / Accepted: 6 August 2026 / Published: 13 August 2026
(This article belongs to the Special Issue Advances in Cryosphere Monitoring: Integrating Multi-Source Remote Sensing and AI Technologies)
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Abstract

Snow disasters constitute a major natural hazard in Northwestern China, where heavy snowfall, blowing snow, and avalanches pose significant threats to infrastructure and socioeconomic activities. A scientific assessment of regional snow disaster risk is therefore critical for disaster prevention, spatial planning, and sustainable development. This study integrates multi-source remote sensing and geographic data to develop a comprehensive risk assessment method. By entropy weight method (EWM), we construct an assessment model that quantifies the combined hazard potential of heavy snowfall, blowing snow, and avalanches. The results reveal a significant spatial correlation among the three primary hazard types. The average potential hazard intensity of heavy snowfall is greater than that of blowing snow, which in turn exceeds that of avalanches. Spatially, the comprehensive snow disaster risk is most severe in the Altai Mountains, the Ili River valley, and the Tacheng region. A moderate-to-high risk level is distributed across the southwestern valleys and the foothills of the northeastern mountains. In contrast, the lowest risk areas are concentrated in certain interior valleys and the leeward slopes of the Junggar Basin. The resulting regional risk zoning was evaluated using receiver operating characteristic (ROC) curve analysis and disaster records. The model achieved an area under the receiver operating characteristic curve (AUC) of 0.871 and an overall accuracy of 84.3%, indicating good spatial discrimination between high- and low-risk zones. These metrics support the application of the framework to regional snow disaster risk assessment.
Keywords: heavy snowfall; avalanches; blowing snow; model validation; multi-source remote sensing; northwestern China; risk assessment; snow disasters heavy snowfall; avalanches; blowing snow; model validation; multi-source remote sensing; northwestern China; risk assessment; snow disasters

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MDPI and ACS Style

He, W.; Hao, X.; Liu, F.; Shao, D.; Wang, W.; Zhao, J.; Liu, Y.; Yang, Q.; Wang, J.; Che, T. Integrating Multi-Source Remote Sensing and Geospatial Data for Snow Disaster Risk Assessment in Northwestern China. Remote Sens. 2026, 18, 2723. https://doi.org/10.3390/rs18162723

AMA Style

He W, Hao X, Liu F, Shao D, Wang W, Zhao J, Liu Y, Yang Q, Wang J, Che T. Integrating Multi-Source Remote Sensing and Geospatial Data for Snow Disaster Risk Assessment in Northwestern China. Remote Sensing. 2026; 18(16):2723. https://doi.org/10.3390/rs18162723

Chicago/Turabian Style

He, Wenxin, Xiaohua Hao, Fenggui Liu, Donghang Shao, Weiguo Wang, Jing Zhao, Yan Liu, Qian Yang, Jian Wang, and Tao Che. 2026. "Integrating Multi-Source Remote Sensing and Geospatial Data for Snow Disaster Risk Assessment in Northwestern China" Remote Sensing 18, no. 16: 2723. https://doi.org/10.3390/rs18162723

APA Style

He, W., Hao, X., Liu, F., Shao, D., Wang, W., Zhao, J., Liu, Y., Yang, Q., Wang, J., & Che, T. (2026). Integrating Multi-Source Remote Sensing and Geospatial Data for Snow Disaster Risk Assessment in Northwestern China. Remote Sensing, 18(16), 2723. https://doi.org/10.3390/rs18162723

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