Spatial heterogeneity of landslide distribution and its drivers in the Yangtze River Basin: a remote sensing and GIS-based multi-factor analysis
IntroductionThe Yangtze River Basin (YRB) is a region of immense economic and ecological significance in China, whose complex topography and climatic variability render it particularly susceptible to landslide disasters.MethodsIn this study, landslide spatial density (LSD) is adopted as a quantitati...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2025.1576700/full |
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| author | Yun Liu Yun Liu Yun Liu Xibin Han Xibin Han Xiaodong Cui Xiaohu Li Xiaohu Li Haiyan Jin Haiyan Jin |
| author_facet | Yun Liu Yun Liu Yun Liu Xibin Han Xibin Han Xiaodong Cui Xiaohu Li Xiaohu Li Haiyan Jin Haiyan Jin |
| author_sort | Yun Liu |
| collection | DOAJ |
| description | IntroductionThe Yangtze River Basin (YRB) is a region of immense economic and ecological significance in China, whose complex topography and climatic variability render it particularly susceptible to landslide disasters.MethodsIn this study, landslide spatial density (LSD) is adopted as a quantitative indicator and multiple linear regression analysis alongside the geographic detector method are employed to evaluate the influence of natural and anthropogenic factors on LSD. A Composite Human Activity Intensity Index (CHAII) is developed from nighttime light intensity, population density, and distances to impermeable surfaces and cultivated land. Factors analyzed include CHAII, slope, topographic ruggedness, precipitation, and distances to river and fault lines. ResultsResults reveal that precipitation and distance to fault are the most significant drivers of LSD across the YRB, with precipitation exhibiting the highest explanatory power. CHAII, precipitation, and topographic ruggedness show strong positive correlations with LSD, whereas slope, distance to river, and distance to fault are negatively correlated. Notably, slopes of 20°–30° correspond to reduced LSD, suggesting a localized mitigating effect. Regionally, intense precipitation in the upper YRB substantially amplifies landslide risk even under low levels of human activity, whereas in the middle YRB natural and anthropogenic factors jointly influence LSD, reflecting a transitional zone. In the lower YRB, interactions between human activity and natural factors become more pronounced, increasing spatial heterogeneity of LSD.DiscussionThe findings provide important scientific insights for landslide risk management and contribute to the sustainable development of the YRB. |
| format | Article |
| id | doaj-art-94a5cdb5c3d04cc0a5e18e409e113ace |
| institution | DOAJ |
| issn | 2296-665X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Environmental Science |
| spelling | doaj-art-94a5cdb5c3d04cc0a5e18e409e113ace2025-08-20T03:21:39ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2025-06-011310.3389/fenvs.2025.15767001576700Spatial heterogeneity of landslide distribution and its drivers in the Yangtze River Basin: a remote sensing and GIS-based multi-factor analysisYun Liu0Yun Liu1Yun Liu2Xibin Han3Xibin Han4Xiaodong Cui5Xiaohu Li6Xiaohu Li7Haiyan Jin8Haiyan Jin9State Key Laboratory of Submarine Geoscience, Hangzhou, ChinaSecond Institute of Oceanography, Ministry of Natural Resources, Hangzhou, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, ChinaState Key Laboratory of Submarine Geoscience, Hangzhou, ChinaSecond Institute of Oceanography, Ministry of Natural Resources, Hangzhou, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, ChinaState Key Laboratory of Submarine Geoscience, Hangzhou, ChinaSecond Institute of Oceanography, Ministry of Natural Resources, Hangzhou, ChinaSecond Institute of Oceanography, Ministry of Natural Resources, Hangzhou, ChinaKey Laboratory of Marine Ecosystem Dynamics, Ministry of Natural Resources, Hangzhou, ChinaIntroductionThe Yangtze River Basin (YRB) is a region of immense economic and ecological significance in China, whose complex topography and climatic variability render it particularly susceptible to landslide disasters.MethodsIn this study, landslide spatial density (LSD) is adopted as a quantitative indicator and multiple linear regression analysis alongside the geographic detector method are employed to evaluate the influence of natural and anthropogenic factors on LSD. A Composite Human Activity Intensity Index (CHAII) is developed from nighttime light intensity, population density, and distances to impermeable surfaces and cultivated land. Factors analyzed include CHAII, slope, topographic ruggedness, precipitation, and distances to river and fault lines. ResultsResults reveal that precipitation and distance to fault are the most significant drivers of LSD across the YRB, with precipitation exhibiting the highest explanatory power. CHAII, precipitation, and topographic ruggedness show strong positive correlations with LSD, whereas slope, distance to river, and distance to fault are negatively correlated. Notably, slopes of 20°–30° correspond to reduced LSD, suggesting a localized mitigating effect. Regionally, intense precipitation in the upper YRB substantially amplifies landslide risk even under low levels of human activity, whereas in the middle YRB natural and anthropogenic factors jointly influence LSD, reflecting a transitional zone. In the lower YRB, interactions between human activity and natural factors become more pronounced, increasing spatial heterogeneity of LSD.DiscussionThe findings provide important scientific insights for landslide risk management and contribute to the sustainable development of the YRB.https://www.frontiersin.org/articles/10.3389/fenvs.2025.1576700/fullYangtze River BasinLandslidehuman activitiesspatial heterogeneitymultiple linear Regressiongeographic detector |
| spellingShingle | Yun Liu Yun Liu Yun Liu Xibin Han Xibin Han Xiaodong Cui Xiaohu Li Xiaohu Li Haiyan Jin Haiyan Jin Spatial heterogeneity of landslide distribution and its drivers in the Yangtze River Basin: a remote sensing and GIS-based multi-factor analysis Frontiers in Environmental Science Yangtze River Basin Landslide human activities spatial heterogeneity multiple linear Regression geographic detector |
| title | Spatial heterogeneity of landslide distribution and its drivers in the Yangtze River Basin: a remote sensing and GIS-based multi-factor analysis |
| title_full | Spatial heterogeneity of landslide distribution and its drivers in the Yangtze River Basin: a remote sensing and GIS-based multi-factor analysis |
| title_fullStr | Spatial heterogeneity of landslide distribution and its drivers in the Yangtze River Basin: a remote sensing and GIS-based multi-factor analysis |
| title_full_unstemmed | Spatial heterogeneity of landslide distribution and its drivers in the Yangtze River Basin: a remote sensing and GIS-based multi-factor analysis |
| title_short | Spatial heterogeneity of landslide distribution and its drivers in the Yangtze River Basin: a remote sensing and GIS-based multi-factor analysis |
| title_sort | spatial heterogeneity of landslide distribution and its drivers in the yangtze river basin a remote sensing and gis based multi factor analysis |
| topic | Yangtze River Basin Landslide human activities spatial heterogeneity multiple linear Regression geographic detector |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2025.1576700/full |
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