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Landslides triggered by the 2010 Yushu earthquake (revised after Xu et al. 2013a). Upper-right inset shows major events of or near Tibet in recent years. a Epicenter of the 2010 Mw 6.9 Yushu earthquake; b epicenter of the 2008 Mw 7.9 Wenchuan earthquake; c epicenter of the 2001 Mw 7.8 Kokoxili earthquake; d epicenter of the 1997 Mw 7.6 Manyi earthquake; e epicenter of the 2008 Mw 7.1 Yutian earthquake; BHB the Bayan Har block; QB Qiangtang block; F1 the Xianshuihe fault zone, the Garzê-Yushu fault is a segment of the Xianshuihe fault; F2 the Longmenshan thrust belt; F3 the Eastern Kunlun fault; JG Jiegu Town, county station of the Yushu County; JL Jielong Town; GY Guoyangyansongduo Village. Beach balls, indicating earthquake focal mechanisms, are downloaded from http://www.globalcmt.org/CMTsearch.html
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The April 14, 2010 Yushu, China, earthquake (Mw 6.9) triggered a great number of landslides. At least 2,036 co-seismic landslides, with a total coverage area of 1.194 km2, were delineated by visual interpretation of aerial photographs and satellite images taken following the earthquake, and verified by field inspection. Based on the mapping results...
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... shown in Fig. 2, the 2,036 landslides are distributed in an approximately rectangle of 1,455.3 km 2 . The total superficial area of these landslides is about 1.194 km 2 . Shallow and disrupted landslides are dominant, also including rock falls, deep-seated landslides, liq- uefaction-induced landslides, and compound landslides ( Xu et al. 2013a). The main co- seismic surface rupture is in approximately alignment with the central line of the rectangle aforementioned (Fig. 2). Most of the co-seismic landsides occurred in clusters near the surface rupture ...
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... shown in Fig. 2, the 2,036 landslides are distributed in an approximately rectangle of 1,455.3 km 2 . The total superficial area of these landslides is about 1.194 km 2 . Shallow and disrupted landslides are dominant, also including rock falls, deep-seated landslides, liq- uefaction-induced landslides, and compound landslides ( Xu et al. 2013a). The main co- seismic surface rupture is in approximately alignment with the central line of the rectangle aforementioned (Fig. 2). Most of the co-seismic landsides occurred in clusters near the surface rupture ...
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... is widely recognized that lithology plays an important role in co-seismic landslides occurrence, because strength structure, permeability, and composition, etc. of soil or rocks that constituting slopes determine the probability of landslide occurrence. From the geo- logical map at a scale of 1:200,000 of the China Geological Survey (Fig. 7), the lithology of the study area is divided into eleven categories (Table 3): Q 4 h, Q 4 al-pl, N, T 3 b, T 3 kn 3 , T 3 kn 2 , T 3 kn 1 , T 2 jl 2 , T 2 jl 1 , C-P, and magmatic rocks. The lithology map, originally in vector format, is converted into raster format at 5 9 5 m resolution using the GIS software. As shown in Table 3 and Figs. 5f and 6f, the units Q 4 al-pl, N, and T 3 kn 1 (classes 2, 3, and 7) have higher LAP and LND than other units. The unit of N is composed of quartz sandstone, breccia, and T 3 kn 1 unit is composed of feldspathic sandstone, siltstone, slate, limestone, phyllite, which have low shear strength and are heavily fractured. In addition, Q 4 al-pl unit is composed of alluvium, fluvial deposits, and gravel, often distributed in valleys. Those places with these geological units are often landslide accumulation areas. Table 2 4.3 Landslide concentration versus earthquake parameters Strong negative correlations are present between LAP and LND and the distance from main surface ruptures (Figs. 5g, 6g). The spatial distribution map (Fig. 2) shows that landslides are concentrated along the main seismic surface ruptures. Buffer zones for distance to the surface rupture are set to 500 m, and 21 intervals are obtained. Most landslides (1,187 landslides or 58.3 % of the total landslide number) occur within 2.5 km from the main surface ruptures. These landslides have an aggregate total area of 0.82 km 2 (68.8 % of the total), indicating that the landslides relatively close to the surface ruptures are on average also relatively larger. Few landslides occur more than 5 km from the surface ...
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... infer that two reasons account for landslide number, landslide area, LAP, and LND on the North side being higher than on the South side. Firstly, the average slope angle on the North side (18.57°) is greater than on the South side (14.01°). There were the tectonic activity differences of the two sides: the North side is located on the Bayan Har block, which has experienced several big earthquakes whereas the South side is located on the Qiangtang block, which is more quietly and less earthquake events along its boundary in recent decades. These large earthquakes (Fig. 2) including the May 12, Wenchuan Mw 7.9 earthquake, the March 21, 2008 Yutian Mw 7.1 earthquake, the November 14, 2001 Kokoxili Mw 7.8 earthquake, and the November 8, 1997 Manyi Mw 7.6 earthquake ( Xu et al. 2013f). Nevertheless, the spatial distributions of landslides triggered by the Yushu earthquake are largely similar on either side of the surface ...
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... Yushu earthquake occurred on the Garzê-Yushu fault, a sinistral strike-slip fault on the western segment of the Xianshuihe fault zone; 40 km west of Jiegu Town, Yushu County, Qinghai Province, in the eastern Tibetan Plateau. After the quake, the Jiegu and Jielong towns were severely affected, and a 300°-striking, 65-km-long surface rupture zone was seen along the fault. The surface rupture zone consists of shear, transtensional, trans- pressional, and tension cracks, as well as mole tracks in right-stepovers and small pull- aparts in left-stepovers between en echelon cracks with left-lateral components ( Xu et al. 2010a). The average left-lateral slip is 1 m with a maximum slip of 2.4 m. The surface rupture zone can be divided into two relatively independent sections: the Jielong section and Jiegu section. The former is 15 km long with a maximum left-lateral slip of 0.66 m, while the latter is about 31 km long with a maximum left-lateral slip of 2.4 m, located near the Guoyangyansongduo Village. The two independent sections correspond to a Mw 6.4 sub-event and to a Mw 6.9 sub-event, respectively (Fig. 2). The Mw 6.4 sub-event was initiated on the Jielong sub-fault near the epicenter, which is dominated by left-lateral slip with normal slip component. The other sub-event triggered left-lateral slip on the Jiegu sub-fault to produce the Mw 6.9 sub-event. ( Xu et al. 2010aXu et al. , 2013aPan et al. 2010;Wu et al. 2010;Chen et al. ...
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... from surface rupture/m (1): 0-500; (2): 500-1,000; (3): 1,000-1,500; (4): 1,500-2,000; (5): 2,000-2,500; (6): 2,500-3,000; (7): 3,000-3,500; (8): 3,500-4,000; (9): 4,000-4,500; (10): 4,500-5,000; (11): 5,000-5,500; (12): 5,500-6,000; (13): 6,000-6,500; (14): 6,500-7,000; (15): 7,000-7,500; (16): 7,500-8,000; (17): 8,000-8,500; (18): 8,500-9,000; (19): 9,000-9,500; (20): 9,500-10,000; (21) together form the boundary fault system of the of Bayan Har block (Fig. 2). The left-lateral slip for those ruptures along the Garzê-Yushu fault and the Eastern Kunlun fault and the reverse slip for the 2008 Wenchuan rupture along the Longmenshan thrust belt may indicate that the southeastward block motion controls the faulting behavior along its boundary fault system ( Xu et al. 2010a). As of April 25, 2010 at 15:00 (Beijing time), 1,467 aftershocks were recorded, 13 aftershocks with magnitude Ms C 3.0, with the strongest measured as Ms 6.2 on April 14, 2010 at 09:25:17.8 (Beijing ...
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On April 20, 2013, a Mw 6.6 earthquake struck Lushan County of Sichuan Province, China, about 80 km southwest of the epicenter of the 12 May 2008 Wenchuan Mw 7.9 event. It triggered a large number of landslides in a broad area, causing causality and injuries and damages to roads, drains, dwellings, and infrastructures. Field investigations of cosei...
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... The results of these studies are essential for disaster prevention and mitigation in the affected areas. In addition, due to the tight relationship among coseismic landslide distribution, seismogenic structure, and seismic intensity, a complete inventory of coseismic landslides can also provide an important basis for understanding the seismogenic fault and seismic rupture mechanism (He et al. 2021a;Valagussa et al. 2019;Wu et al. 2018;Xu and Xu 2014). ...
... Correlations between earthquake magnitude (Mw) and coseismic landslide distribution area (a) and the landslide number (b). The cases shown by green circles reference Keefer (1984), Keefer (2002), Rodrıguez et al. (1999), Xu and Xu (2014), and He and Xu (2022) Landslides 20 • (2023) ...
On June 10, 2022, an earthquake swarm including three major earthquakes with magnitudes of Ms5.8, Ms6.0, and Ms5.2 occurred in Maerkang, Sichuan, China. According to statistics, at least 650 landslides have been triggered by this earthquake, with a total area of 1.2 km2. In this study, the spatial distribution of these landslides and their correlation with seismic, topographic, and geological factors were analyzed based on the coseismic landslide inventory. The results show that landslides are mainly distributed on the northeast side of the Songgang-Fubianhe fault (SG-FBHF), which is a VII intensity area. The closer to the epicenter, the more concentrated the landslide distribution. The landslide density increases significantly with increasing slope. The strata of the Upper Triassic Zhuwo Formation are more prone to coseismic landslide occurrence. Our results, when combined with the focal mechanism solution, precise location of aftershocks, and geological characteristics of the SG-FBHF, suggest that this earthquake is a left-lateral strike-slip earthquake along the SG-FBHF, and the seismogenic fault is slightly tilted to the northeast. In addition, nearly 70% of coseismic landslides are concentrated in the extreme seismic area of ~ 225km2, indicating that the seismic energy release is highly concentrated. This work analyzed the distribution of landslides triggered by a moderately strong earthquake swarm, providing a typical case for researchers to understand the spatial distribution pattern of earthquake-triggered landslides and a scientific support for disaster prevention of coseismic landslides in southwestern Sichuan, China.
... The LND and LAD reach their maximums in the PGA range of 0.16 g-0.2 g, peaking at 3.9/km 2 and 0.86% respectively. Coseismic landslides are controlled by seismogenic faults in earthquake events [33,[35][36][37]. We constructed 60 bins at 1 km intervals along the strike of the seismogenic fault to analyze the relationships between landslide abundance and distance to the seis- Coseismic landslides are controlled by seismogenic faults in earthquake events [33,[35][36][37]. ...
... Coseismic landslides are controlled by seismogenic faults in earthquake events [33,[35][36][37]. We constructed 60 bins at 1 km intervals along the strike of the seismogenic fault to analyze the relationships between landslide abundance and distance to the seis- Coseismic landslides are controlled by seismogenic faults in earthquake events [33,[35][36][37]. We constructed 60 bins at 1 km intervals along the strike of the seismogenic fault to analyze the relationships between landslide abundance and distance to the seismogenic fault. ...
... For example, the landslides triggered by thrust earthquakes are prone to occur in the hanging wall of the seismogenic fault, and the attenuation rate of the landslides in the hanging wall is significantly lower than that in the footwall with the increase in the distance from the fault [10,46]. However, for strike-slip earthquakes, there is little difference in the development of landslides on both sides of the fault, and landslides are often densely distributed along the seismogenic fault [24,35,45]. The landslides caused by the 1999 Chichi earthquake were mostly concentrated in the hanging wall, while there were fewer landslides in the footwall [47]. ...
At 17:00 (UTC+8) on 1 June 2022, an Ms 6.1 reverse earthquake struck Lushan County, Ya’an City, Sichuan Province. This earthquake event had a focal depth of 10 km and the epicenter was located at 30.37° N and 102.94° E. The purpose of this study is to document a comprehensive coseismic landslide inventory for this event and analyze the distribution pattern and factors controlling the landslides. After careful visual interpretations, this quake event was determined to have in total triggered about 2352 landslides in an area of 3900 km2, including both shallow disrupted landslides and collapses, for which the spatial distribution was statistically related to regional topography, geology, and seismicity. Notably, a vast majority of the landslides were located on the NW plate of the seismogenic fault, and were distributed in the area with a seismic intensity of VII. In addition, coseismic landslides were more likely to appear in areas with high altitude, relief, and large slope. The landslide area density (LAD) increased with an increase in the above factors and is explained by an exponential relationship, indicating that the occurrence of coseismic landslides in this area was more easily affected by topographic factors than seismic factors. Most small-scale landslides were clustered in the ridge area, which shows the seismic amplification effects of mountain slopes. Due to the impact of seismic wave propagation direction, hillslopes facing northeast-east (NE-E) were more prone to collapse than southwest-facing ones. Based on the distribution pattern of the landslides, we suggest that the seismogenic fault of this event was NW dipping. These findings indicate that it is effective to identify the dipping of seismogenic faults using the spatial distribution pattern of coseismic landslides.
... For a better understanding of the detailed information of earthquakeinduced landslides, including the spatial location, the type, the geometrical parameters, traditional site investigation; remote sensing (RS) technology and geographic information system (GIS) technology have been used in practice (Huang 2000;Keefer 2002;Mohammad et al. 2006;Masahiro and Hiroshi 2004;Zhang and Wang 2007;Huang and Li 2009;Dai et al. 2011;Yin et al. 2009;Gorum et al. 2011;Huang et al. 2013;Li et al. 2013a;Xu et al. 2014;Xu et al. 2014aXu et al. , 2014bXu et al. 2015;Guo et al. 2017;Rosser and Carey 2017). Furthermore, based on comprehensive analysis of statistic data and actual conditions, the spatial distribution characteristics, the initiation mechanism and causative factors, have been summarized (Keefer 2000;Masahiro and Hiroshi 2004;Sato et al. 2005;Meunier et al. 2007;Rajabi et al. 2010;Wang et al. 2010;Chen et al. 2011;Lee 2013;Zhang et al. 2013;Zheng et al. 2013;Yin et al. 2014;Xu et al. 2014a, Xu et al. 2014a, 2014bXu and Xu 2014c;Tang et al. 2015;Xu et al. 2016;Tian et al. 2017). An important subject is the assessment of the stability or performance of the slope under seismic conditions, whereby the existing analytical methods can be classified into three different categories (Tropeano et al. 2017). ...
The main objective of this study is to evaluate the performances of different earthquake-induced landslides susceptibility mapping models at mountainous regions in China. At first, 160 earthquake-induced landslide points were identified from field investigations. Concurrently, based on the results of a literature review and the field investigation, 12 influencing factors were considered, and the corresponding thematic layers were generated using geographic information system (GIS) technology. Subsequently, 20 groups with a fixed number of cells were collected as a common training dataset for the two different models, based on a random selection from the entire database (including landslide cells and no-landslide cells). The neural network (NN) model and logistic regression (LR) model were developed with R software. Finally, earthquake-induced landslides susceptibility maps of Wenchuan county were produced, very low, low, medium, high and very high susceptibility zones cover. The validation results indicate that the landslide data from field investigations are in good agreement with the evaluation results, and the LR model has a slightly better prediction than the NN model in this case. In general, the NN model and LR models are satisfactory for susceptibility mapping of earthquake-induced landslides at mountainous regions.
... Slope position can be quantified by the Topographic Position Index (TPI), which describes the difference between a cell elevation value and the mean of the neighborhood around the cell. Along with the steepness (slope angle) of each cell, slope position can be classified into six categories including valley (extreme low TPI value), lower slope (moderately low TPI value), gentle slope (TPI value around 0, slope angle ≤ 5°), steep slope (TPI value around 0, slope angle > 5°), upper slope (moderately high TPI value), and ridge (extreme high TPI value) (Weiss 2001;Jenness et al. 2013). The drainage distributions in the study area are shown in Fig. 4. (5 m). ...
... 1. Landslide length and width are thought to be the corresponding values of the ellipse or rectangle with the equivalent area and perimeter approximating to the real landslide (Taylor and Malamud 2012;Taylor et al. 2015). 2. The length of the landslide is defined as the length between the crown and the toe along the sliding direction, and the width is the ratio of the landslide area and length (average width) (Xu and Xu 2014). 3. The length and width of the landslide are the corresponding values of the landslide minimum bounding rectangle along the sliding direction (Fig. 6). ...
... According to the statistics for the landslides induced by the 1994 Mw 6.7 Northridge earthquake in the Santa Susana quadrangle, CA, USA, Parise and Jibson (2000) insisted that the landslide aspect ratio is about 2.6 on average. Xu and Xu (2014) analyzed the 2036 coseismic landslides triggered by the 2010 Mw 6.9 Yushu, China earthquake, yielding landslide aspect ratios from 1.5 to 32.8 with average 4.15. Based on the coseismic landslides of the 2010 Mw 7.0 Haiti earthquake, Xu et al. (2014a) show that the aspect ratios range from 1.37 to 53.4 with an average value of 3.76. ...
Geometric parameters are useful for characterizing earthquake-triggered landslides. This paper presents a detailed statistical analysis on this issue using the landslide inventory of the 2013, Minxian, China Mw 5.9 earthquake. Based on GIS software and a 5-m resolution DEM, geometric parameters of 635 coseismic landslides (with areas larger than 500 m²) were obtained, including height, length, width, reach angle (arc tangent of the height-length ratio), and aspect ratio (length-width ratio). The fitting relationship of height and length from these data is H = 0.6164L + 0.4589, with an average reach angle of 31.65°. The landslide aspect ratios concentrate in the range of 1.4∼2.6, with an average of 2.11. According to the plane geometric shapes and aspect ratios, the landslides are classified into four categories: transverse landslide (LA1, L/W ≤ 0.8), isometric landslide (LA2, 0.8 < L/W ≤ 1.2), longitudinal landslide (LA3, 1.2 < L/W ≤ 3), and elongated landslide (LA4, L/W > 3). Statistics of these four types of landslides versus ten classified control factors (elevation, slope angle, slope aspect, curvature, slope position, distance to drainages, lithology, seismic intensity, peak ground acceleration, and distance to seismogenic fault) are used to examine their possible correlations and the landslide-prone areas, which would be helpful to the landslide disaster mitigation in the affected area.
... Each definition was classified as either frequency-independent or frequency-dependent according to whether the entire accelerogram is employed in the calculation of duration or whether it is first passed through a narrowband fitter. Furthermore, each definition was also classified according to whether the criteria used to distinguish the strong motion portion of the accelerograms are absolute or their relative values applied to the accelerogram [34][35][36][37][38][39][40]. ...
Earthquake duration is a complex natural phenomenon associated with the sudden energy release induced by fault rupture. The shaking during an earthquake is a result of the primary, secondary and surface waves. This study is aimed at establishing the relationship between earthquake duration and other seismic parameters: magnitude, peak ground acceleration, focal distance, fault length in relation to landslides generated by the major earthquakes. To achieve this objective, we made an intensive review of published data on major earthquakes (Mw ≥ 6.6) that generated landslides between 1998 and 2015 in the world. The results reveal that magnitude, focal length and focal depth times fault length are strong determinants of earthquake duration. However, it is noted that peak ground acceleration (PGA) and focal depth do not necessarily determine the duration of earthquake shaking. It is also observed that duration of an earthquake is moderately correlated to area affected by earthquake induced landslides. Additionally, much as the number of landslides produced during and/or after an earthquake does not necessarily augment with increasing duration majority of the investigated major earthquakes that produced great damage, with respect to landslides, were noticed to have lasted for not more than 60 seconds.
The Zhaotong area in Yunnan Province stands out as one of the most susceptible areas to landslide disasters. The landslide susceptibility of the Zhaotong area can be attributed to its steep terrain, fractured rock formations and strong rainfall, compounded by its frequent seismic activity. This study utilized landslide data provided by the Zhaotong City Natural Resources and Planning Bureau and visually interpreted from high-resolution satellite images of Google Earth to establish the landslide database of the Zhaotong area, including 161 landslides and 3646 potential geological disasters. The distribution characteristics and possible influencing factors of landslides within the Zhaotong area were analyzed using the aforementioned data. The results show that the spatial distribution of landslides and potential geological disasters is roughly consistent; the most concentrated landslides occurred at the junction of Yiliang County, Zhaotong City, and Daguan County, indicating the necessity to enhance surveillance of these landslide-prone areas. The relationship of landslide locations and different influencing factors suggests that elevation, slope angle, and distance to rivers are closely related to landslide occurrence. Landslides are more likely to occur in areas with lower elevations with slope angles ranging from 10° to 40° and near river channels.
On August 8, 2017, a magnitude Mw6.5 (Ms7.0) earthquake occurred in Jiuzhaigou County, Aba Prefecture, in the northern part of Sichuan Province, China, with a focal depth of 20 km and an epicenter located at (33.2°N, 103.8°E). Due to the significant magnitude of the earthquake, a large number of coseismic landslides were triggered. Despite previous research conducted by experts on the landslides caused by the Jiuzhaigou earthquake, the actual number of landslides has been severely underestimated in the previously published papers. Through field surveys and visual interpretation of high-resolution remote sensing images before and after the mainshock, we have established a detailed inventory of earthquake-induced landslides. The results indicate that the event caused a minimum of 9428 landslides covering a total area of 18.82 km². These landslides are mainly distributed in the IX intensity area of the earthquake. The landslides mainly consist of medium-sized landslides and debris flows. They predominantly occur in areas with an altitude ranging from 2600 m to 3600 m, with slopes greater than 30° and facing east and southeast. The Lower Carboniferous and Middle Carboniferous formations are more prone to triggering landslides, and landslides are more concentrated within 1 km of roads and in forested areas. Additionally, as the distance from roads and the epicenter increases, the values of LAP and LND decrease, indicating a positive correlation between the two. There are more landslides within 2 km from the fault and within a range of 6 km–9 km from the epicenter. In conclusion, this study provides a comprehensive landslide inventory with broader coverage and increased accuracy. It also conducts a comprehensive analysis of the spatial distribution patterns of landslides. This contributes to a deeper understanding of the causes of coseismic landslides and further research on the impact of landslides in affected areas.
The tectonic deformation on the eastern margin of the Qaidam Basin, which has preserved complete sedimentary records, significantly influences the evolutionary model of the northeastern margin of the Tibetan Plateau. However, the deformation history in this area during the Holocene remains unclear. This study is based on the high‐precision digital elevation model obtained through drone mapping technology, which identifies three active faults on the eastern margin of the Qaidam Basin: the Xiariha Fault (XRHF) and Yingdeerkang Fault Yingdeerkang Fault (YKF) are NW‒SE‐orientated dextral faults, whereas the Reshui‐Taosituohe Fault (RTF) is a nearly east‒west‐orientated sinistral fault. Based on the optically stimulated luminescence dating of the landform surfaces, the rates of strike‐slip offset are as follows: those of the XRHF range from 1.12 ± 0.07 to 1.68 ± 0.12 mm/yr and those of the YKF are from 0.99 ± 0.06 to 2.29 ± 0.13 mm/yr. Recent paleoseismic events occurred along the RTF at approximately 714–1,792 years BP and at 700 ± 18 years BP, implying a recurring millennial pattern. Together, these faults possibly form a complex cross‐fault system along the southeastern edge of the basin, heightening seismic risk. Deformation in the western part of the northeastern Tibetan Plateau is driven by slip on the Altyn Tagh Fault and compression in the Qaidam Basin. The central part experiences slip on the East Kunlun Fault, along with secondary faults, shortening, and block rotation. The eastern part primarily experiences slip along the Haiyuan Fault.
The occurrence of landslide disasters causes huge economic losses and casualties. Although many achievements have been made in predicting the probability of landslide disasters, various factors such as the scale and spatial location of landslide geological disasters should still be fully considered. Further research on how to quantitatively characterize the susceptibility of landslide geological disasters is necessarily important. To this end, taking the Wenchuan earthquake as the research area and extracting eight influencing factors, including terrain information entropy (Ht), lithology, distance from rivers, distance from faults, vegetation coverage (NDVI), distance from roads, peak ground motion acceleration (PGA), and annual rainfall, a landslide susceptibility prediction model was hereby established based on LSTM-RF-MDBN, a landslide susceptibility prediction map was drawn, and the spatial distribution characteristics of landslide disasters were analyzed. The results showed that (1) LSTM had good prediction results for the eight influencing factors, with an average prediction accuracy of 85%; (2) compared with models such as DNN and LR for predicting landslide disaster points, the AUC value of RF for predicting landslide point positions reached 0.88, presenting a higher accuracy compared to other models; (3) the AUC value of the landslide susceptibility prediction model based on LSTM-RF-MDBN reached 0.965, which had a high accuracy in predicting landslide susceptibility. Overall, the research results can provide a scientific basis for selecting the best strategy for landslide disaster warning, prevention, and mitigation.
