Relationships between landslide types and topographic attributes in a loess catchment, China

Topographic attributes have been identified as the most important factor in controlling the initiation and distribution of shallow landslides triggered by rainfall.As a result,these landslides influence the evolution of local surface topography.In this research,an area of 2.6 km 2 loess catchment in the Huachi County was selected as the study area locating in the Chinese Loess Plateau.The landslides inventory and landslide types were mapped using global position system(GPS) and field mapping.The landslide inventory shows that these shallow landslides involve different movement types including slide,creep and fall.Meanwhile,main topographic attributes were generated based on a high resolution digital terrain model(5 m × 5 m),including aspect,slope shape,elevation,slope angle and contributing area.These maps were overlaid with the spatial distributions of total landslides and each type of landslides in a geographic information system(GIS),respectively,to assess their spatial frequency distributions and relative failure potentials related to these selected topographic attributes.The spatial analysis results revealed that there is a close relation between the topographic attributes of the postlandsliding local surface and the types of landslide movement.Meanwhile,the types of landslide movement have some obvious differences in local topographic attributes,which can influence the relative failure potential of different types of landslides.These results have practical significance to mitigate natural hazard and understandgeomorphologic process in thick loess area.     

霍西煤矿区地表滑坡灾害敏感性数值建模与等级划分

本文以山西省霍西煤矿区为研究区,利用遥感和GIS方法对滑坡灾害的敏感性进行了数值建模与定量评价。利用交叉检验方法构建了径向基核函数支持向量机滑坡敏感性评价模型,并基于拟合精度对模型进行了定量评价;对各评价因子在模型中的重要性进行对比分析;基于空间分辨率为30m的评价因子,通过径向基核函数支持向量机模型获得了霍西煤矿区滑坡敏感性指数值,并利用分位数法将霍西煤矿区的滑坡敏感性分为极高、高、中和低4个等级。结果表明：拟合精度建模阶段和验证阶段分别为87.22%和70.12%;与滑坡敏感性关系最密切的5个评价因子依次是岩性、距道路距离、坡向、高程和土地利用类型;极高和高敏感区域分布了93.49%的滑坡点,面积占总面积的50.99%,是比较合理的分级方案。本研究不仅可以为研究区人工边坡调查和煤矿资源合理开采提供借鉴,对相似矿区的相关工作也具有参考价值。     

Rapid susceptibility mapping of co-seismic landslides triggered by the 2013 Lushan Earthquake using the regression model developed for the 2008 Wenchuan Earthquake

The primary objective of landslide susceptibility mapping is the prediction of potential landslides in landslide-prone areas.The predictive power of a landslide susceptibility mapping model could be tested in an adjacent area of similar geoenvironmental conditions to find out the reliability.Both the 2008 Wenchuan Earthquake and the 2013 Lushan Earthquake occurred in the Longmen Mountain seismic zone,with similar topographical and geological conditions.The two earthquakes are both featured by thrust fault and similar seismic mechanism.This paper adopted the susceptibility mapping model of co-seismic landslides triggered by Wenchuan earthquake to predict the spatial distribution of landslides induced by Lushan earthquake.Six influencing parameters were taken into consideration: distance from the seismic fault,slope gradient,lithology,distance from drainage,elevation and Peak Ground Acceleration(PGA).The preliminary results suggested that the zones with high susceptibility of coseismic landslides were mainly distributed in the mountainous areas of Lushan,Baoxing and Tianquan counties.The co-seismic landslide susceptibility map was completed in two days after the quake and sent to the field investigators to provide guidance for rescue and relief work.The predictive power of the susceptibility map was validated by ROC curve analysis method using 2037 co-seismic landslides in the epicenter area.The AUC value of 0.710 indicated that the susceptibility model derived from Wenchuan Earthquake landslides showed good accuracy in predicting the landslides triggered by Lushan earthquake.     

Landslide Susceptibility Mapping along Bhalubang–Shiwapur Area of Mid-Western Nepal Using Frequency Ratio and Conditional Probability Models

Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang–Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and to predict future occurrence of the landslides, landslide susceptibility mapping(LSM) of this region was carried out using frequency ratio(FR) and weights-of-evidence(W of E) models. These models are easy to apply and give good results. For this, landslide inventory map of the area was prepared based on the aerial photo interpretation, from previously published/unpublished reposts, and detailed field survey using GPS. About 332 landslides were identified and mapped, among which 226(70%) were randomly selected for model training and the remaining 106(30%) were used for validation purpose. A spatial database was constructed from topographic, geological, and land cover maps. The reclassified maps based on the weight values of frequency ratio and weights-of-evidence were applied to get final susceptibility maps. The resultant landslide susceptibility maps were verified andcompared with the training data, as well as with the validation data. From the analysis, it is seen that both the models were equally capable of predicting landslide susceptibility of the region(W of E model(success rate = 83.39%, prediction rate = 79.59%); FR model(success rate = 83.31%, prediction rate = 78.58%)). In addition, it was observed that the distance from highway and lithology, followed by distance from drainage, slope curvature, and slope gradient played major role in the formation of landsides. The landslide susceptibility maps thus produced can serve as basic tools for planners and engineers to carry out further development works in this landslide prone area.     

Post-earthquake Rainfall-triggered Slope Stability Analysis in the Lushan Area

The "4.20" Lushan earthquake in Sichuan province, China has induced a large amount of geological hazards and produced abundant loose materials which are prone to post-earthquake rainfalltriggered landslides. A detailed landslide inventory was acquired through post-earthquake emergent field investigation and high resolution remote sensing interpretation. The rainfall analysis was conducted using historical rainfall records during the period from 1951 to 2010. Results indicate that the average annual rainfall distribution is heterogeneous and the largest average annual rainfall occurs in Yucheng district. The Stability Index MAPping(SINMAP)model was adopted to assess and analyze the postearthquake slope stability under different rainfall scenarios(light rainfall, moderate rainfall, heavy rainfall, and rainstorm). The model parameters were calibrated to reflect the significant influence of strong earthquakes on geological settings. The slope stability maps triggered by different rainfall scenarios wereproduced at a regional scale. The effect of different rainfall conditions on the slope stability is discussed.The expanding trend of the unstable area was quantitatively assessed with the different critical rainfall intensity. They provide a new insight into the spatial distribution and characteristics of postearthquake rainfall-triggered landslides in the Lushan seismic area. An increase of rainfall intensity results in a significant increase of unstable area. The heterogeneous distribution of slope instability is strongly correlated with the distribution of earthquake intensity in spite of different rainfall conditions. The results suggest that the both seismic intensity and rainfall are two crucial factors for postearthquake slope stability. This study provides important references for landslide prevention and mitigation in the Lushan area after earthquake.     

Co-seismic landslide inventory and susceptibility mapping in the 2008 Wenchuan earthquake disaster area, China

The Ms 8.0 May 12,2008 Wenchuan earthquake triggered tens of thousands of landslides.The widespread landslides have caused serious casualties and property losses,and posed a great threat to post-earthquake reconstruction.A spatial database,inventoried 43,842 landslides with a total area of 632 km 2,was developed by interpretation of multi-resolution remote sensing images.The landslides can be classified into three categories:swallow,disrupted slides and falls;deep-seated slides and falls,and rock avalanches.The correlation between landslides distribution and the influencing parameters including distance from co-seismic fault,lithology,slope gradient,elevation,peak ground acceleration(PGA) and distance from drainage were analyzed.The distance from co-seismic fault was the most significant parameter followed by slope gradient and PGA was the least significant one.A logistic regression model combined with bivariate statistical analysis(BSA) was adopted for landslide susceptibility mapping.The study area was classified into five categories of landslide susceptibility:very low,low,medium,high and very high.92.0% of the study area belongs to low and very low categories with corresponding 9.0% of the total inventoried landslides.Medium susceptible zones make up 4.2% of the area with 17.7% of the total landslides.The rest of the area was classified into high and very high categories,which makes up 3.9% of the area with corresponding 73.3% of the total landslides.Although the susceptibility map can reveal the likelihood of future landslides and debris flows,and it is helpful for the rebuilding process and future zoning issues.     

Size distribution of submarine landslides along the middle continental slope of the East China Sea

This paper investigates the size distribution of submarine landslides on the middle continental slope of the East China Sea (ECS) using the size of the landslide source regions. Geomorphometric mapping is used to identify 102 mass movements from multibeam bathymetric data and to extract morphological information about the head scarps and side walls. These mass movements have areas ranging between 0.06 km² and 15.51 km² and volumes between 0.002 km³ and 2 km³. The area vs volume relationship of these failure scarps is approximately linear, suggesting a fairly uniform failure thickness in each event with scarce deep excavating landslides. The cumulative area distribution of the slope failures can be described by an inverse power law. The submarine landslides on the mid-ECS continental slope could be considered as a large-scale self-organizing system because they have the characteristics of a dissipative system in a critical state.     

Slope Instability on Pyroclastic Deposits： Landslide Distribution and Risk Mapping in Zacapoaxtla, Sierra Norte De Puebla, Mexico

Introduction The impact produced by landsliding in diverse regions of the world has given rise to the development and implementation of different methods, techniques and tools to understand the mechanisms of movements involved, as well as to create maps o…     

Size and spatial distribution of landslides induced by the 2015 Gorkha earthquake in the Bhote Koshi river watershed

The Mw 7.8 Gorkha earthquake in Nepal on April 25, 2015, produced thousands of landslides in the Himalayan mountain range. After the earthquake, two field investigations along Araniko Highway were conducted. Then, using remote sensing technology and geographic information system(GIS)technology, 1481 landslides were identified along the Bhote Koshi river. Correlations between the spatial distribution of landslides with slope gradient and lithology were analyzed. The power-law relationship of the size distribution of earthquake-induced landslides was examined in both the Higher Himalaya and Lesser Himalaya. Possible reasons for the variability of the power exponent were explored by examining differences in the geological situations of these areas. Multi-threshold cellular automata were introduced to model the complexity of system components. Most of the landslides occurred at slope gradients of 30°–40°, and the landslide density was positively correlated with slope gradient. Landslides in hard rock areas were more common than in soft rock areas. The cumulative number-area distribution of landslides induced by the Gorkha earthquake exhibited a negative power-law relationship, but the power exponents were different: 1.13 in the Higher Himalaya, 1.36 and Lesser Himalaya. Furthermore,the geological conditions were more complex and varied in the Lesser Himalaya than in the Higher Himalaya, and the cellular automata simulation results indicated that, as the complexity of system components increased, the power exponent increased.Therefore, the variability of the power exponent of landslide size distribution should ascribe to the complexity of geological situations in the Bhote Koshi river watershed.     

Regolith thickness modeling using a GIS approach for landslide distribution analysis,NW Himalayas

Regolith thickness is considered as a contributing factor for the occurrence of landslides. Although, mostly it is ignored because of complex nature and as it requires more time and resources for investigation. This study aimed to appraise the role of regolith thickness on landslide distribution in the Muzaffarabad and surrounding areas, NW Himalayas. For this purpose regolith thickness samples were evenly collected from all the lithological units at representative sites within different slope and elevation classes in the field. Topographic attributes (slope, aspect, drainage, Topographic Wetness Index, elevation and curvature) were derived from the Digital Elevation Model (DEM) (12.5 m resolution). ArcGIS Model Builder was used to develop the regolith thickness model. Stepwise regression technique was used to explore the spatial variation of regolith thickness using topographic attributes and lithological units. The derived model explains about 88% regolith thickness variation. The model was validated and shows good agreement (70%) between observed and predicted values. Subsequently, the derived regolith model was used to understand the relationship between regolith thickness and landslide distribution. The analysis shows that most of the landslides were located within 1–5 m regolith thickness. However, landslide concentration is highest within 5–10 m regolith thickness, which shows that regolith thickness played a significant role for the occurrence of landslide in the studied area.     

Risk assessment of secondary geological disasters induced by the Yushu earthquake

The Yushu Ms 7.1 earthquake occurred on April 14,2010 in Qinghai Province,China.It induced a mass of secondary geological disasters,such as collapses,landslides,and debris flows.Risk assessment maps are important for geological disaster prevention and mitigation,and also can serve as a guide for post-earthquake reconstruction.Firstly,a hazard assessment index system of secondary geological disasters in the earthquake region was built in this paper,which was based on detailed analysis of environmental and triggering factors closely related to geological disasters in the study area.GIS technology was utilized to extract and analyze the assessment index.Hazard assessment maps of secondary geological disasters were obtained by spatial modeling and overlaying analysis.Secondly,an analysis of the vulnerability of hazard bearing bodies in the area was conducted,important information,such as, population density,percentage of arable land, industrial and agricultural outputs per unit area were regarded as assessment indices to evaluate socioeconomic vulnerability.Thirdly,the risk level of secondary geological disasters of the area was obtained by the formula:Risk=Hazard×Vulnerability. Risk assessment maps were categorized into four levels,including"low","moderate","high"and"very high".These results show that some urban areas are at very high risk,including Jiegu,Chengwen,Xiaxiula and Sahuteng towns.This research can provide some references and suggestions to improve decisionmaking support for emergency relief and post- earthquake reconstruction in the study area.     

Deriving the slope-mean shielded astronomical solar radiation spectrum and slope-mean possible sunshine duration spectrum over the Loess Plateau

Solar radiation is often shielded by terrain relief, especially in mountainous areas, before reaching the surface of the Earth. The objective of this paper is to study the spatial structures of the shielded astronomical solar radiation(SASR) and the possible sunshine duration(PSD) over the Loess Plateau. To this end, we chose six test areas representing different landforms over the Loess Plateau and the software package of Matlab was used as the main computing platform. In each test area, 5-m-resolution digital elevation model established from 1:10,000 scale topographic maps was used to compute the corresponding slope, SASR and PSD. Then, we defined the concepts of the slope-mean SASR spectrum and the slope-mean PSD spectrum, and proposed a method to extract them from the computed slope, SASR and PSD over rectangular analysis windows. Using this method, we found both spectrums in a year or in a season for each of the four seasons in the six test areas. Each spectrum was found only when the area of the corresponding rectangular analysis window was greater than the corresponding stable area of the spectrum. The values of the two spectrums decreased when the slope increased.Furthermore, the values of the stable areas of the spectrums in a year or in a season were positively correlated with the variable coefficients of the slope or the profile curvature. The values of the stable areas of the two spectrums in a year or in a season may represent the minimum value of test areas for corresponding future research on the spatial structures of the SASR or PSD. All the findings herein suggest that the spatial structures of the PSD and the SASR are caused by the interactions between solar radiation and terrain relief and that the method for extracting either spectrum is effective for detecting their spatial structures. This study may deepen our understanding of the spatial structure of solar radiation and help us further explore the distribution of solar energy in mountainous regions.     

GIS-based earthquake-triggered landslide hazard zoning using contributing weight model

Earthquake-triggered landslides have aroused widespread attention because of their tremendous ability to harm people's lives and properties.The best way to avoid and mitigate their damage is to develop landslide hazard maps and make them available to the public in advance of an earthquake.Future construction can then be built according to the level of hazard and existing structures can be retrofit as necessary.During recent years various approaches have been made to develop landslide hazard maps using statistical analysis or physical models.However,these methods have limitations.This study introduces a new GIS-based approach,using the contributing weight model,to evaluate the hazard of seismically-induced landslides.In this study,the city and surrounding area of Dujiangyan was selected as the research area because of its moderate-high seismic activity.The parameters incorporated into the model that related to the probability of landslide occurrence were:slope gradient,slope aspect,geomorphology,lithology,base level,surface roughness,earthquake intensity,fault proximity,drainage proximity,and road proximity.The parameters were converted into raster data format with a resolution of 25×25m2 pixels.Analysis of the GIS correlations shows that the highest earthquake-induced landslide hazard areas are mainly in the hills and in some of the moderately steep mountainous areas of central Dujiangyan.The highest hazard zone covers an area of 11.1% of the study area,and the density distribution of seismically-induced landslides was 3.025/km2 from the 2008 Wenchuan earthquake.The moderately hazardous areas are mainly distributed within the moderately steep mountainous regions of the northern and southeastern parts of the study area and the hills of the northeastern part;covering 32.0% of the study area and with a density distribution of 2.123/km2 resulting from the Wenchuan earthquake.The lowest hazard areas are mainly distributed in the topographically flat plain in the northeastern part and some of the relatively gently slopes in the moderately steep mountainous areas of the northern part of Dujiangyan and the surrounding area.The lowest hazard areas cover 56.9% of the study area and exhibited landslide densities of 0.941/km2 and less from the Wenchuan earthquake.The quality of the hazard map was validated using a comparison with the distribution of landslides that were cataloged as occurring from the Wenchuan earthquake.43.1% of the study area consists of high and moderate hazardous zones,and these regions include 83.5% of landslides caused by the Wenchuan earthquake.The successful analysis shows that the contributing weight model can be effective for earthquake-triggered landslide hazard appraisal.The model's results can provide the basis for risk management and regional planning is.     

Landslide inventory and susceptibility assessment using multiple statistical approaches along the Karakoram highway,northern Pakistan

China-Pakistan Economic Corridor(CPEC)is a framework of regional connectivity,which will not only benefit China and Pakistan but will have positive impact on Iran,Afghanistan,India,Central Asian Republic,and the region.The surrounding area in CPEC is prone to frequent disruption by geological hazards mainly landslides in northern Pakistan.Comprehensive landslide inventory and susceptibility assessment are rarely available to utilize for landslide mitigation strategies.This study aims to utilize the high-resolution satellite images to develop a comprehensive landslide inventory and subsequently develop landslide susceptibility maps using multiple techniques.The very high-resolution(VHR)satellite images are utilized to develop a landslide inventory using the visual image classification techniques,historic records and field observations.A total of 1632 landslides are mapped in the area.Four statistical models i.e.,frequency ratio,artificial neural network,weights of evidence and logistic regression were used for landslide susceptibility modeling by comparing the landslide inventory with the topographic parameters,geological features,drainage and road network.The developed landslides susceptibility maps were verified using the area under curve(AUC)method.The prediction power of the model was assessed by the prediction rate curve.The success rate curves show 93%,92.8%,92.7%and 87.4%accuracy of susceptibility maps for frequency ratio,artificial neural network,weights of evidence and logistic regression,respectively.The developed landslide inventory and susceptibility maps can be used for land use planning and landslide mitigation strategies.     

Investigation and Assessment of Landslides and Debris Flows in Sichuan Province of China by Remote Sensing Technique

Taking TM images, ETM images, SPOT images, aerial photos and other remote sensing data as fundamental sources, this research makes a thorough investigation on landslides and debris flows in Sichuan Province, China, using the method of manual interpretation and taking topography maps as references after the processes of terrain correction, spectral matching, and image mosaic. And then, the spatial characteristics of landslides and debris flows in the year of 2005 are assessed and made into figures. The environmental factors which induce landslides and debris flows such as slope, vegetation coverage, lithology, rainfall and so on are obtained by GIS spatial analysis method. Finally, the relationships of landslides or debris flows with some environmental factors are analyzed based on the grade of each environmental factor. The results indicate： 1） The landslides and debris flows are mainly in the eastern and southern area of Sichuan Province, however, there are few landslides and debris flows in the western particularly the northwestern Sichuan. 2） The landslides and debris flows of Sichuan Province are mostly located in the regions with small slope degree. The occurring rate of debris flow reduces with the increase of the vegetation coverage degree, but the vegetation coverage degree has little to do with the occurrence of landslide. The more rainfall a place has, the easier the landslides and debris flows take place.     

Regional scale rainfall- and earthquake-triggered landslide susceptibility assessment in Wudu County, China

Wudu County in northwestern China frequently experiences large-scale landslide events.High-magnitude earthquakes and heavy rainfall events are the major triggering factors in the region.The aim of this research is to compare and combine landslide susceptibility assessments of rainfalltriggered and earthquake-triggered landslide events in the study area using Geographical Information System(GIS) and a logistic regression model.Two separate susceptibility maps were produced using inventories reflecting single landslide-triggering events,i.e.,earthquakes and heavy rain storms.Two groups of landslides were utilized: one group containing all landslides triggered by extreme rainfall events between 1995 and 2003 and the other group containing slope failures caused by the 2008 Wenchuan earthquake.Subsequently,the individual maps were combined to illustrate the locations of maximum landslide probability.The use of the resulting three landslide susceptibility maps for landslide forecasting,spatial planning and for developing emergency response actions are discussed.The combined susceptibility map illustrates the total landslide susceptibility in the study area.     

Susceptibility assessment of landslides caused by the wenchuan earthquake using a logistic regression model

The Wenchuan earthquake on May 12, 2008 caused numerous collapses, landslides, barrier lakes, and debris flows. Landslide susceptibility mapping is important for evaluation of environmental capacity and also as a guide for post-earthquake reconstruction. In this paper, a logistic regression model was developed within the framework of GIS to map landslide susceptibility. Qingchuan County, a heavily affected area, was selected for the study. Distribution of landslides was prepared by interpretation of multi-temporal and multi-resolution remote sensing images (ADS40 aerial imagery, SPOT5 imagery and TM imagery, etc.) and field surveys. The Certainly Factor method was used to find the influencial factors, indicating that lithologic groups, distance from major faults, slope angle, profile curvature, and altitude are the dominant factors influencing landslides. The weight of each factor was determined using a binomial logistic regression model. Landslide susceptibility mapping was based on spatial overlay analysis and divided into five classes. Major faults have the most significant impact, and landslides will occur most likely in areas near the faults. Onethird of the area has a high or very high susceptibility, located in the northeast, south and southwest, including 65.3% of all landslides coincident with the earthquake. The susceptibility map can reveal the likelihood of future failures, and it will be useful for planners during the rebuilding process and for future zoning issues.     

三峡库区大型-特大型层状岩质滑坡成因模式及地质特征分析

三峡库区大型-特大型滑坡发育，尤以层状岩质滑坡的危害性大。因库区各段地质条件差异使得滑坡成因模式各不相同，这影响了滑坡的运动形式和岩土体解体程度。在收集三峡库区51处典型的大型-特大型层状岩质滑坡调查资料基础上，根据堆积岩体结构和区段地质条件反推该段滑坡破坏成因模式，而不同成因模式下的滑坡坡体渗透性不同，分析已有滑坡对库水位变动存在的复活响应差异，据此得出以下结论:①在成因模式上，除顺层滑移型滑坡在库区中均有分布外，从库首至库尾随着岩层倾角的逐渐减缓，滑坡成因模式从崩塌型、反倾弯曲型逐渐过渡到平推式；②在坡体渗透性上，成因模式造成的岩体结构变化与坡体中的泥质含量共同作用，导致顺层滑移型滑坡前后缘渗透性存在较大差异；反倾型滑坡渗透性则整体变化较小；③在库水位变动影响下，不同坡体渗透性与滑面形态共同决定了滑坡的复活变形差异。      

GIS based spatial data analysis for landslide susceptibility mapping

Landslide susceptibility map delineates the potential zones for landslides occurrence. The paper presents a statistical approach through spatial data analysis in GIS for landslide susceptibility mapping in parts of Sikkim Himalaya. Six important causative factors for landslide occurrences were selected and corresponding thematic data layers were prepared in GIS. Topographic maps,satellite image,field data and published maps constitute the input data for thematic layer preparation. Numerical weights for different categories of these factors were determined based on a statistical approach and the weighted thematic layers were integrated in GIS environment to generate the landslide susceptibility map of the area. The landslide susceptibility map classifies the area into five different landslide susceptible zones i.e.,very high,high,moderate,low and very low. This map was validated using the existing landslide distribution in the area.     

Earthquake-triggered landslides affecting a UNESCO Natural Site: the 2017 Jiuzhaigou Earthquake in the World National Park,China

On August 8~(th), 2017, an Ms 7.0 magnitude earthquake occurred in Jiuzhaigou County, northern Sichuan Province, China. The Jiuzhaigou Valley World National Park was the most affected area due to the epicentre being located in the scenic area of the park. Understanding the distribution characteristics of landslides triggered by earthquakes to help protect the natural heritage sites in Jiuzhaigou Valley remains a scientific challenge. In this study, a relatively complete inventory of the coseismic landslides triggered by the earthquake was compiled through the interpretation of high-resolution images combined with a field investigation. The results indicate thatcoseismic landslides not only are concentrated in Rize Gulley, Danzu Gully and Zezhawa Gully in the study area but also occur in the front part of Shuzheng Gully along the road network(from the entrance of Jiuzhaigou Valley to Heye Village). The landslides predominantly occur on the east-and southeastfacing slopes in the study area, which is a result of the integrated action of the valley direction and fault movement direction. The back-slope effect and the slope structure caused the difference in coseismic landslide distribution within the three gullies(Danzu Gully, Rize Gully, and Zezhawa Gully) near the inferred fault. In addition, the topographic position index was used to analyse the impact of microlandforms on earthquake-triggered landslides by considering the effect of the slope angle. The study results reveal a higher concentration of landslides in the slope position class of the middle slope(30°-50°) in Jiuzhaigou Valley. These findings can provide scientific guidance for the protection of natural heritage sites and post-disaster reconstruction in Jiuzhaigou Valley.