Distribution Patterns of Moraines and Susceptibility Assessment of Geological Hazards in the Shangri-La Region, Northwest Yunnan

The Shangri-La region in northwest Yunnan preserves extensive glacial moraines, which provide abundant loose material for landslides and debris flows. Mapping these moraines is therefore critical for susceptibility assessment. In this study, we used remote sensing interpretation to extract the spatial distribution of moraines. We then applied the Analytic Hierarchy Process (AHP) to eight factors—elevation, slope, curvature, vegetation cover, lithology, moraine distribution, rainfall, and human activities—and built a susceptibility model within a GIS framework. A Monte Carlo simulation was also conducted to test the sensitivity of the factor weights to potential uncertainties in expert judgments. The results show that moraines cover about 186.7 km2 of the study area. Rainfall intensity and moraine distribution emerged as the two most influential factors. The simulation gave weights that differ from the standard AHP by less than 1.6%, suggesting the results are stable. The resulting susceptibility map divides the area into four zones: non-susceptible, low, moderate, and high susceptibility. The high-susceptibility zone covers 1656.48 km2 (14.26% of the total area), mainly in high-altitude, steep terrain where moraines are present. The model performed reasonably well in validation, with an ROC curve AUC of 0.807. These findings could support local hazard prevention and land-use planning.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2026-08-03
DOI
https://doi.org/10.3390/app16157707
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Distribution Patterns of Moraines and Susceptibility Assessment of Geological Hazards in the Shangri-La Region, Northwest Yunnan

Liurunxuan Chen, Shitao Zhang, Ruohan Zuo, Haonan Yin et al.
Applied Sciences
Landslides and related hazards
article

Distribution Patterns of Moraines and Susceptibility Assessment of Geological Hazards in the Shangri-La Region, Northwest Yunnan

Liurunxuan Chen, Shitao Zhang, Ruohan Zuo, Haonan Yin, Weiqi Wang, Yukai Hu
article en

Abstract

The Shangri-La region in northwest Yunnan preserves extensive glacial moraines, which provide abundant loose material for landslides and debris flows. Mapping these moraines is therefore critical for susceptibility assessment. In this study, we used remote sensing interpretation to extract the spatial distribution of moraines. We then applied the Analytic Hierarchy Process (AHP) to eight factors—elevation, slope, curvature, vegetation cover, lithology, moraine distribution, rainfall, and human activities—and built a susceptibility model within a GIS framework. A Monte Carlo simulation was also conducted to test the sensitivity of the factor weights to potential uncertainties in expert judgments. The results show that moraines cover about 186.7 km2 of the study area. Rainfall intensity and moraine distribution emerged as the two most influential factors. The simulation gave weights that differ from the standard AHP by less than 1.6%, suggesting the results are stable. The resulting susceptibility map divides the area into four zones: non-susceptible, low, moderate, and high susceptibility. The high-susceptibility zone covers 1656.48 km2 (14.26% of the total area), mainly in high-altitude, steep terrain where moraines are present. The model performed reasonably well in validation, with an ROC curve AUC of 0.807. These findings could support local hazard prevention and land-use planning.

Applied SciencesVol. 16(15)
Kunming University of Science and Technology (CN)
Chengdu University of Technology
Sustainable cities and communities
Openalex Percentile: Top 6%
Landslides and related hazards
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.