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Uncertainties in landslide susceptibility prediction modeling:A review on the incompleteness of landslide inventory and its influence rules

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Geoscience Frontiers 2024年第6期15卷 80-104页

作者： Faming Huang Daxiong Mao Shui-Hua Jiang Chuangbing Zhou Xuanmei Fan Ziqiang Zeng Filippo Catani Changshi Yu Zhilu Chang Jinsong Huang Bingchen Jiang Yijing Li School of Infrastructure Engineering Nanchang UniversityNanchang 330031China State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Chengdu University of TechnologyChengduSichuan 610059China Science and Technology Department of Jiangxi Province Nanchang 330046China Department of Geosciences University of PadovaPadovaItaly Information Engineering School Nanchang UniversityNanchang 330031China Discipline of Civil Surveying and Conditioning EngineeringPriority Research Centre for Geotechnical Science and EngineeringUniversity of NewcastleNSWAustralia

landslide inventory is an indispensable output variable of landslide susceptibility prediction(LSP)***,the influence of landslide inventory incompleteness on LSP and the transfer rules of LSP resulting error in the model have not been *** Xunwu County,China,as an example,the existing landslide inventory is first obtained and assumed to contain all landslide inventory samples under ideal conditions,after which different landslide inventory sample missing conditions are simulated by random *** includes the condition that the landslide inventory samples in the whole study area are missing randomly at the proportions of 10%,20%,30%,40%and 50%,as well as the condition that the landslide inventory samples in the south of Xunwu County are missing in ***,five machine learning models,namely,Random Forest(RF),and Support Vector Machine(SVM),are used to perform ***,the LSP results are evaluated to analyze the LSP uncertainties under various *** addition,this study introduces various interpretability methods of machine learning model to explore the changes in the decision basis of the RF model under various *** show that(1)randomly missing landslide inventory samples at certain proportions(10%–50%)may affect the LSP results for local areas.(2)Aggregation of missing landslide inventory samples may cause significant biases in LSP,particularly in areas where samples are missing.(3)When 50%of landslide samples are missing(either randomly or aggregated),the changes in the decision basis of the RF model are mainly manifested in two aspects:first,the importance ranking of environmental factors slightly differs;second,in regard to LSP modelling in the same test grid unit,the weights of individual model factors may drastically vary.

关键词： landslide susceptibility prediction landslide inventory Machine learning interpretability SHapley additive explanations Partial dependence plot

Distribution patterns of landslides triggered by the 2022 Ms 6.8 Luding earthquake,Sichuan,China

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Journal of Mountain Science 2023年第3期20卷 607-623页

作者： ZHANG Jian-qiang YANG Zong-ji MENG Qing-kai WANG Jiao HU Kai-heng GE Yong-gang SU Feng-huan ZHAO Bo ZHANG Bo JIANG Ning HUANG Yu MING Zai-yang ZHANG Yi-fan LIU Zhen-xing WU Chun-hao ZHOU Wen-tao LIANG Xin-yue SUN Yu-qing YANG Lian-bing YAO Hong-kun FENG Pei-hua LIU Jia-li Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu 610041China University of Chinese Academy of Sciences Bejing 100049China East China University of Technology Nanchang 330013China Institute of Geographic Sciences and Natural Resources Research Beijing 100101China Chongqing Jiaotong University Chongqing 400074China

At 12:52 pm on September 5,2022,an Ms 6.8 earthquake occurred in Luding County,Sichuan Province,*** on high-resolution aerial photographs and satellite imageries obtained after the earthquake,as well as field investigation,a total of 8685 earthquake-triggered landslides(EQTLs)were *** landslides covered an area of 30.7km^(2),with a source area of 9.4 km^(2).These EQTLs were mainly distributed in areas with a seismic intensity of VIII and *** of the landslides were small and medium in size,and their types included landslide,rockfall,and rock *** landslide distributions were found,EQTLs were distributed along the Xianshuihe fault,landslide area decreased gradually with an increased distance to the fault;EQTLs were distributed along the Daduhe River and roads;besides,landslide distribution was associated with ground deformation caused by the ***’characteristics indicated that,a large number of EQTLs were located near the foot of the slope;the full area of EQTLs and their source area followed a power *** study concluded that Luding EQTLs were greater in number and area but relatively smaller in terms of affected *** on geo-hazards post-earthquake and risk assessment were proposed in the earthquake-stricken area to support the rehabilitation and reconstruction.

关键词： 2022 Luding earthquake Earthquaketriggered landslide landslide inventory Distribution patterns

landslides Triggered by the 3 August 2014 Ludian(China) Mw 6.2 Earthquake: An Updated inventory and Analysis of Their Spatial Distribution

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Journal of Earth Science 2020年第4期31卷 853-866页

作者： Weiying Wu Chong Xu Xiaoqing Wang Yingying Tian Fei Deng Institute of Earthquake Forecastings China Earthquake Administration Beijing 100036China Institute of Crustal Dynamics China Earthquake AdministrationBeijing 100085China Key Laboratory of Active Tectonics and Volcano Institute of GeologyChina Earthquake AdministrationBeijing 100029China

The 3 August 2014 Ludian, Yunnan, China Mw 6.2(Ms 6.5) earthquake triggered a large number of coseismic landslides. Based on pre-and post-quake high-resolution optical satellite images, this study established a new, complete and objective database of these landslides with field investigations. The updated inventory shows that this earthquake triggered at least 12 817 landslides with a total occupation area of 16.33 km2, covering a nearly circular area about 600 km2, which all exceed those in our previous work and other relevant studies. In addition, we used this database to examine the correlations of the landslides with topographic, geologic, and seismic factors. Results show that the landslides occurred mostly at places with slope gradients 10o–40o, showing an increase tendency with steeper slopes. Affected by the propagation direction of the earthquake rupture, the eastward-facing slopes are more prone to landsliding. The differences between the landslide susceptibility in different strata indicate that lithology is also an important controlling factor. The landslide density of the places with peak ground acceleration(PGA) greater than 0.16 g is obviously larger than those with PGA less than 0.16 g. Meanwhile, the greater the distance from the epicenter, the lower the susceptibility of landslides is. This study suggests that when using satellite images to create coseismic landslide inventories, it should meet certain conditions, including high resolution, whole coverage, and timely data collection. The correct criteria of coseismic landslide inventorying also should be followed. Such inventories can provide a reliable basis for hazard assessment of earthquake-triggered landslides and other quantitative studies.

关键词： 2014 Ludian earthquake coseismic landslides landslide inventory spatial distribution

landslides triggered by the 1970 Ms 7.7 Tonghai earthquake in Yunnan,China: an inventory, distribution characteristics, and tectonic significance

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Journal of Mountain Science 2022年第6期19卷 1633-1649页

作者： CUI Yu-long HU Jun-hong XU Chong MIAO Hai-bo ZHENG Jun School of Civil Engineering and Architecture Anhui University of Science and TechnologyHuainan 232001China National Institute of Natural Hazards Ministry of Emergency Management of ChinaBeijing 100085China Department of Civil Engineering Zhejiang UniversityHangzhou 310058China

The 1970 Tonghai earthquake, which occurred on January 5, 1970, in Tonghai County, Yunnan Province, China, triggered a large number of landslides. Since the occurrence of the earthquake, there have been a huge number of research reports on the seismogenic structure and earthquake mechanism, but rare reports on the seismic landslides. As the largest earthquake recorded in the Qujiang fault zone, the study on the coseismic landslides triggered by this earthquake are of great significance to the prevention and mitigation of earthquake-induced landslides in this region. In this study, we established a coseismic landslide inventory for the VⅢ–X seismic intensity areas of the Ms 7.7 Tonghai earthquake, and conducted spatial analysis on the coseismic landslides, mainly having analyzed the effect of the topographic factors, geological factors, and seismic factors on the development of the coseismic landslides. To enhance the understanding of this earthquake, we converted the earthquake epicenter and magnitude with empirical formulas based on the distributions and areas of the coseismic landslides. Comparing with coseismic landslides in other earthquake-hit areas, we found the capability that this earthquake could induce landslides is low. This study provides a useful supplement to the global coseismic landslide inventories and could be the basic data for seismic landslide assessment in this earthquake-prone region.

关键词： 1970 Tonghai Ms 7.7 earthquake Coseismic landslides landslide inventory Spatial analysis Tectonic significance

landslides Triggered by the 2020 Qiaojia M_(w)5.1 Earthquake, Yunnan, China: Distribution, Influence Factors and Tectonic Significance

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Journal of Earth Science 2021年第5期32卷 1056-1068页

作者： Xiangli He Chong Xu Wenwen Qi Yuandong Huang Jia Cheng Xiwei Xu Qi Yao Yongkun Lu Boyang Dai National Institute of Natural Hazards Ministry of Emergency Management of ChinaBeijing 100085China Key Laboratory of Compound and Chained Natural Hazards Dynamics(Under Construction) Ministry of Emergency Management of ChinaBeijing 100085China China University of Geosciences Beijing 100083China China Earthquake Networks Center Beijing 100045China Yunnan Earthquake Agency Kunming 650224China

On May 18, 2020, an M_(w)5.1 earthquake occurred in Qiaojia County, Yunnan Province, China. This moderate-sized event triggered massive coseismic landslides, resulting in some damage. In this work, through visual interpretation of high-resolution(0.8–2 m) Gaofen satellite images before and after the earthquake, 167 landslides were delineated, 18 of which were inspected in the field. Using the landslide number density(LND) and landslide area percentage(LAP), we characterized the spatial distribution of these landslides, and analyzed their possible influence factors and tectonic significance. The results show that these landslides are distributed mostly in the NW-SE direction, roughly parallel to the long axis of seismic intensity zones and the strike of the Xiaohe-Baogunao fault(XBF). The LND and LAP decrease with increasing distances to the fault and from the epicenter to fault ends of the XBF. These permit to suggest that the seismogenic fault of the Qiaojia earthquake is likely a hidden branch of the XBF. All of the landslides induced by this event occurred in the region with the seismic intensity of six degrees or greater of the 2014 M_(w)6.2 Ludian earthquake. Therefore, it was inferred that the 2020 Qiaojia earthquake was probably the subsequent release of accumulated elastic strain after the 2014 Ludian earthquake in a same tectonic stress regime.

关键词： Qiaojia earthquake landslide inventory spatial distribution seismogenic fault Ludian earthquake

Detailed inventory Mapping and Spatial Analyses to landslides Induced by the 2013 Ms 6.6 Minxian Earthquake of China

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Journal of Earth Science 2016年第6期27卷 1016-1026页

作者： Yingying Tian Chong Xu Xiwei Xu Jian Chen Key Laboratory of Active Tectonics and Volcano Institute of GeologyChina Earthquake Administration School of Engineering and Technology China University of Geosciences

On July 22, 2013, an earthquake （Ms 6.6） occurred in Minxian, Gansu Province of China, causing a large number of landslides. Based on high resolution remote sensing images before and after this event, we made the visual interpretation to these coseismic landslides, and prepared a detailed inventory. The inventory registers totally 6 478 landslides in the study area. Of them, 3 322 landslides are larger than 100 m2. Based on 5 m resolution DEM, these landslides were used to perform spatial analyses using landslide number density （LND） and landslide area percentage （LAP）. The results show that the highest LND and LAP values are in the elevation range of 2 300-2 500 m and steeper slopes. Slopes facing E, SE, S and SW directions, slopes with larger absolute curvature values, ridges, scopes of gravel beds of Late Pleistocene （Qp） and the VIII-degree seismic intensity are more prone to sliding with high LND and LAP values. The largest LND and LAP values are in the scopes of 0.08 and 0.24 g, respectively. According to landslide distribution, we infer that F2-2 branch of Lintan-Dangchang fault is the seismogenic fault. With the increasing distances to this branch fault and drainages, LND and LAP values tend to decrease.

关键词： Minxian Earthquake landslide inventory spatial analyses landslide number density (LND) landslide area percentage (LAP).

Spatial distribution characteristics of climate-induced landslides in the Eastern Himalayas

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Journal of Mountain Science 2024年第10期21卷 3396-3412页

作者： UWIZEYIMANA David LIU Weiming HUANG Yu HABUMUGISHA Jules Maurice ZHOU Yanlian YANG Zewen State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of Sciences(CAS)Chengdu 610299China China–Pakistan Joint Research Center on Earth Sciences CAS-HECIslamabad 45320Pakistan University of Chinese Academy of Sciences Beijing 100049China

Climate warming is constantly causing hydro-meteorological perturbations,especially in high-altitude mountainous regions,which lead to the occurrences of *** impact of climatic variables(i.e.,precipitation and temperature)on the distribution of landslides in the eastern regions of the Himalayas is poorly *** address this,the current study analyzes the relationship between the spatial distribution of landslide characteristics and climatic variables from 2013 to *** Earth Engine(GEE)was employed to make landslide inventories using satellite *** results show that 2163,6927,and 9601 landslides were heterogeneously distributed across the study area in 2013,2017,and 2021,*** maximum annual temperature was positively correlated with the distribution of landslides,whereas precipitation was found to have a non-significant impact on the landslide ***,most of the landslides occurred in areas with maximum annual precipitation ranging from 800 to 1600 mm and maximum annual temperature above 15℃.However,in certain regions,earthquake disruptions marginally affected the occurrence of *** were highly distributed in areas with elevations ranging between 3000 and 5000 m above sea level,and many landslides occurred near the lower permafrost limit and close to *** latter indicates that temperature change-induced freeze-thaw action influences landslides in the *** changes have shown a positive correlation with the number of landslides within elevations,indicating that temperature affects their spatial *** climate projections suggest that the region will experience further warming,which will increase the likelihood of landslides in the ***,it is crucial to enhance ground observation capabilities and climate datasets to effectively monitor and mitigate landslide risks.

关键词： landslide inventory Climate variables Normalized difference vegetation index Cryosphere Eastern Himalaya

An open-accessed inventory of landslides triggered by the M_(S)6.8 Luding earthquake,China on September 5,2022

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Earthquake Research Advances 2023年第1期3卷 37-44页

作者： Yuandong Huang Chenchen Xie Tao Li Chong Xu Xiangli He Xiaoyi Shao Xiwei Xu Tao Zhan Zhaoning Chen National Institute of Natural Hazards Ministry of Emergency Management of ChinaBeijing100085China Key Laboratory of Compound and Chained Natural Hazards Dynamics Ministry of Emergency Management of ChinaBeijing100085China China University of Geosciences(Beijing) Beijing100083China Institute of Disaster Prevention Sanhe065201China 107 Geological Team Chongqing Bureau of Geology and Minerals ExplorationChongqing401120China School of Emergency Management Science and Engineering University of Chinese Academy of SciencesBeijing100049China

This study constructs a preliminary inventory of landslides triggered by the M_(S) 6.8 Luding earthquake based on field investigation and human-computer interaction visual interpretation on optical satellite *** results show that this earthquake triggered at least 5007 landslides,with a total landslide area of 17.36 km^(2),of which the smallest landslide area is 65 m^(2)and the largest landslide area reaches 120747 m^(2),with an average landslide area of about 3500 m^(2).The obtained landslides are concentrated in the IX intensity zone and the northeast side of the seismogenic fault,and the area density and point density of landslides are 13.8%,and 35.73 km^(-2) peaks with 2 km as the search *** should be noted that the number of landslides obtained in this paper will be lower than the actual situation because some areas are covered by clouds and there are no available post-earthquake remote sensing *** on the available post-earthquake remote sensing images,the number of landslides triggered by this earthquake is roughly estimated to be up to *** study can be used to support further research on the distribution pattern and risk evaluation of the coseismic landslides in the region,and the prevention and control of landslide hazards in the seismic area.

关键词： Luding earthquake landslide inventory Coseismic landslides Visual interpretation Field investigation