Spatial distribution of shallow landslides caused by Typhoon Lekima in 2019 in Zhejiang Province, China

In recent years, the coastal region of Southeast China has witnessed a significant increase in the frequency and intensity of extreme rainfall events associated with landfalling typhoons. The hilly and mountainous terrain of this area, combined with rapid rainfall accumulation, has led to a surge in flash floods and severe geological hazards. On August 10, 2019, Typhoon Lekima made landfall in Zhejiang Province, China, and its torrential rainfall triggered extensive landslides, resulting in substantial damage and economic losses. Utilizing high-resolution satellite images, we compiled a landslide inventory of the affected area, which comprises a total of 2,774 rainfallinduced landslides over an area of 2965 km2. The majority of these landslides were small to mediumsized and exhibited elongated, clustered patterns. Some landslides displayed characteristics of high-level initiation, obstructing or partially blocking rivers, leading to the formation of debris dams. We used the inventory to analyze the distribution pattern of the landslides and their relationship with topographical, geological, and hydrological factors. The results showed that landslide abundance was closely related to elevation, slope angle, faults, and road density. The landslides were predominantly located in hilly and low mountainous areas, with elevations ranging from 150 to 300 m, slopes of 20 to 30 degrees, and a NE-SE aspect. Notably, we observed the highest Landslide Number Density(LND) and Landslide Area Percentage(LAP) in the rhyolite region. Landslides were concentrated within approximately 4 km on either side of fault zones, with their size and frequency negatively correlated with distances to faults, roads, and river systems. Furthermore, under the influence of typhoons, regions with denser vegetation cover exhibited higher landslide density, reaching maximum values in shrubland areas. In areas experiencing significantly increased concentrated rainfall, landslide density also showed a corresponding rise. In terms of spatial distribution, the rainfall-triggered landslides primarily occurred in the northeastern part of the study area, particularly in regions characterized by complex topography such as Shanzao Village in Yantan Town, Xixia Township, and Shangzhang Township. The research findings offer crucial data on the rainfallinduced landslides triggered by Typhoon Lekima, shedding light on their spatial distribution patterns. These findings provide valuable references for mitigating risks and planning reconstruction in typhoon-affected area.

Time-lagged Effects of the Spring Atmospheric Heat Source over the Tibetan Plateau on Summer Precipitation in Northeast China during 1961–2020:Role of Soil Moisture

The spring atmospheric heat source(AHS)over the Tibetan Plateau(TP)has been suggested to affect the Asian summer monsoon and summer precipitation over South China.However,its influence on the summer precipitation in Northeast China(NEC)remains unknown.The connection between spring TP AHS and subsequent summer precipitation over NEC from 1961 to 2020 is analyzed in this study.Results illustrate that stronger spring TP AHS can enhance subsequent summer NEC precipitation,and higher soil moisture in the Yellow River Valley-North China region(YRVNC)acts as a bridge.During spring,the strong TP AHS could strengthen the transportation of water vapor to East China and lead to excessive rainfall in the YRVNC.Thus,soil moisture increases,which regulates local thermal conditions by decreasing local surface skin temperature and sensible heat.Owing to the memory of soil moisture,the lower spring sensible heat over the YRVNC can last until mid-summer,decrease the land–sea thermal contrast,and weaken the southerly winds over the East Asia–western Pacific region and convective activities over the South China Sea and tropical western Pacific.This modulates the East Asia–Pacific teleconnection pattern,which leads to a cyclonic anomaly and excessive summer precipitation over NEC.

Automated machine learning for rainfall-induced landslide hazard mapping in Luhe County of Guangdong Province,China

Landslide hazard mapping is essential for regional landslide hazard management.The main objective of this study is to construct a rainfall-induced landslide hazard map of Luhe County,China based on an automated machine learning framework(AutoGluon).A total of 2241 landslides were identified from satellite images before and after the rainfall event,and 10 impact factors including elevation,slope,aspect,normalized difference vegetation index(NDVI),topographic wetness index(TWI),lithology,land cover,distance to roads,distance to rivers,and rainfall were selected as indicators.The WeightedEnsemble model,which is an ensemble of 13 basic machine learning models weighted together,was used to output the landslide hazard assessment results.The results indicate that landslides mainly occurred in the central part of the study area,especially in Hetian and Shanghu.Totally 102.44 s were spent to train all the models,and the ensemble model WeightedEnsemble has an Area Under the Curve(AUC)value of92.36%in the test set.In addition,14.95%of the study area was determined to be at very high hazard,with a landslide density of 12.02 per square kilometer.This study serves as a significant reference for the prevention and mitigation of geological hazards and land use planning in Luhe County.

Preliminary geological interpretation of long-wavelength magnetic anomalies over China and surrounding regions

Long-wavelength(>500 km)magnetic anomalies originating in the lithosphere were first found in satellite magnetic surveys.Compared to the striking magnetic anomalies around the world,the long-wavelength magnetic anomalies in China and surrounding regions are relatively weak.Specialized research on each of these anomalies has been quite inadequate;their geological origins remain unclear,in particular their connection to tectonic activity in the Chinese and surrounding regions.We focus on six magnetic high anomalies over the(1)Tarim Basin,(2)Sichuan Basin(3)Great Xing’an Range,(4)Barmer Basin,(5)Central Myanmar Basin,and(6)Sunda and Banda Arcs,and a striking magnetic low anomaly along the southern part of the Himalayan-Tibetan Plateau.We have analyzed their geological origins by reviewing related research and by detailed comparison with geological results.The tectonic backgrounds for these anomalies belong to two cases:either ancient basin basement,or subduction-collision zone.However,the geological origins of large-scale regional magnetic anomalies are always subject to dispute,mainly because of limited surface exposure of sources,later tectonic destruction,and superposition of multi-phase events.

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

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 images.The 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 radius.It 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 images.Based on the available post-earthquake remote sensing images,the number of landslides triggered by this earthquake is roughly estimated to be up to 10000.This 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.

Identification and distribution of 13003 landslides in the northwest margin of Qinghai-Tibet Plateau based on human-computer interaction remote sensing interpretation

The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Tibet Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.

Freely accessible inventory and spatial distribution of large-scale landslides in Xianyang City,Shaanxi Province,China

In this study, we used high-resolution optical satellite images on the Google Earth platform to map large-scale landslides in Xianyang City, Shaanxi Province, China. After mapping, a comprehensive and detailed large-scale landslide inventory that contains 2 924 large-scale landslides was obtained. We analyzed the spatial distribu-tion of landslides with seven influencing factors, including elevation, slope angle, aspect, curvature, lithology, distance to a river, and distance to the fault. Landslide Number, Landslide Area, Landslide Number Density(LND), and Landslide Area Percentage(LAP) were selected as indexes for the spatial distribution analysis. The results show that the number and area of landslides in the elevation range of 1 000–1 200 m is the highest. The highest number of landslides was observed in the slope angle of 25°–30°. North-facing slopes are prone to sliding. The area and number of landslides are the largest when the slope curvature ranges from-1.28 to 0. The LND and LAP reach their maxima when the slope curvature is less than-2.56. Areas covered by the Tertiary stratum with weakened fine-grained sandstone and siltstone show the highest LND and LAP values. Regarding distance to a river, the LAP peaks in the range of 300–600 m, whereas the LND peaks in an area larger than 2100 m. The values of LND and LNP rise as the distance from the faults increases, except for the locations 30 km away from active faults. This phenomenon is because active faults in this area pass through the plain areas, while landslides mostly occur in mountainous areas. The cataloging of landslide development in Xianyang City provides a significant scientific foundation for future research on landslides. In addition, the spatial distribution results are useful for landslide hazard prevention decisions and provide valuable references in this area.

Tensile Fractures and in situ Stress Measurement Data Constraints on Cretaceous-Present Tectonic Stress Field Evolution of the Tanlu Fault Zone in Shandong Province,North China Craton

Tectonic stress fields are the key drivers of tectonic events and the evolution of regional structures.The tectonic stress field evolution of the Tanlu fault zone in Shandong Province,located in the east of the North China Craton(NCC),may have preserved records of the NCC’s tectonic history.Borehole television survey and hydraulic fracturing were conducted to analyze the paleo and present tectonic stress fields.Three groups of tensile fractures were identified via borehole television,their azimuths being NNW-SSE,NW-SE and NE-SW,representing multiple stages of tectonic events.Hydraulic fracturing data indicates that the study region is experiencing NEE-SWW-oriented compression and nearly-N-Soriented extension,in accordance with strike-slip and compression.Since the Cretaceous,the orientation of the extensional stress has evolved counterclockwise and sequentially from nearly-NW-SE-oriented to NE-SW-oriented and even nearly N-S-oriented,the stress state having transitioned from strike-slip-extension to strike-slip-compression,in association with the rotating and oblique subduction of the Pacific Plate beneath the NCC,with the participation of the Indian Plate.

Application of logistic regression model for hazard assessment of landslides caused by the 2012 Yiliang Ms 5.7 earthquake in Yunnan Province,China

Accurate assessment of seismic landslides hazard is a prerequisite and foundation for postdisaster relief of earthquakes.An Ms 5.7 earthquake occurring on September 7,2012,in Yiliang County,Yunnan Province,China,triggered hundreds of landslides.To explore the characteristics of coseismic landslides caused by this moderate-strong earthquake and their significance in predicting seismic landslides regionally,this study uses an artificial visual interpretation method based on a planet image with 5-m resolution to obtain the information of the coseismic landslides and establishes a coseismic landslide database containing data on 232 landslides.Nine influencing factors of landslides were selected for this study:elevation,relative elevation,slope angle,aspect,slope position,distance to river system,distance to faults,strata,and peak ground acceleration.The real probability of coseismic landslide occurrence is calculated by combining the Bayesian probability and logistic regression model.Based on the coseismic landslides,the probabilities of landslide occurrence under different peak ground acceleration are predicted using a logistic regression model.Finally,the model established in this paper is used to calculate the landslide probability of the Ludian Ms 6.5 earthquake that occurred in August 2014,78.9 km away from the macro-epicenter of the Yiliang earthquake.The probability is verified by the real coseismic landslides of this earthquake,which confirms the reliability of the method presented in this paper.This study proves that the model established according to the seismic landslides triggered by one earthquake has a good effect on the seismic landslides hazard assessment of similar magnitude,and can provide a reference for seismic landslides prediction of moderate-strong earthquakes in this region.

Lacustrine sedimentary responses to earthquakes—soft-sediment deformation structures since late Pleistocene:A review of current understanding

The traces left by earthquakes in lacustrine sediments are studied to determine the occurrence of ancient earthquakes by identifying seismically induced soft-sediment deformation structures(SSDS).Dating can help reconstruct the relative frequency of earthquakes.Identifying seismically induced seismites,which carry abundant seismic information from numerous SSDS,is both critical and challenging.Studying the deformation mechanism of SSDS and learning about the common criteria of seismically induced SSDS improve the identification of earthquake triggers.With better research into SSDS,seismic events can be effectively captured,and temporal constraints can be carried out by 14C dating and optically stimulated luminescence(OSL)dating to identify and date the occurrence of ancient earthquakes.The present contribution primarily addresses the meaning and mechanism of SSDS and their relationship with earthquake magnitude as well as the common criteria of the SSDS induced by earthquakes.

A catastrophic natural disaster chain of typhoon-rainstorm-landslide-barrier lake-flooding in Zhejiang Province, China

On August 10,2019,due to the effect of a rainstorm caused by Super Typhoon Lekima,a landslide occurred in Shanzao Village,China.It blocked the Shanzao stream,forming a barrier lake,and then the barrier lake burst.This is a rare natural disaster chain of typhoon-rainstorm-landslide-barrier lake-flooding.This study was built on field surveys,satellite image interpretation,the digital elevation model(DEM),engineering geological analysis and empirical regression.The purpose was to reveal the characteristics and causes of the landslide,the features and formation process of the barrier lake and the dam break flooding discharge.The results show that the volume of the landslide deposit is approximately 2.4×105 m3.The burst mode of the landslide dam is overtopping,which took only 22 minutes from the formation of the landslide dam to its overtopping.The dam-break peak flow was 1353 m3/s,and the average velocity was 2.8–3.0 m/s.This study shows that the strongly weathered rock and soil slope has low strength and high permeability under the condition of heavy rainfall,which reminds us the high risk of landslides and the importance of accurate early warning of landslides under heavy rainfalls in densely populated areas of Southeast China,as well as the severity of the disaster chain of typhoon-rainstorm-landslide-barrier lake-flooding.

A review of the influencing factors on teleseismic traveltime tomography

Teleseismic traveltime tomography is an important tool for investigating the crust and mantle structure of the Earth.The imaging quality of teleseismic traveltime tomography is affected by many factors,such as mantle heterogeneities,source uncertainties and random noise.Many previous studies have investigated these factors separately.An integral study of these factors is absent.To provide some guidelines for teleseismic traveltime tomography,we discussed four main influencing factors:the method for measuring relative traveltime differences,the presence of mantle heterogeneities outside the imaging domain,station spacing and uncertainties in teleseismic event hypocenters.Four conclusions can be drawn based on our analysis.(1)Comparing two methods,i.e.,measuring the traveltime difference between two adjacent stations(M1)and subtracting the average traveltime of all stations from the traveltime of one station(M2),reveals that both M1 and M2 can well image the main structures;while M1 is able to achieve a slightly higher resolution than M2;M2 has the advantage of imaging long wavelength structures.In practical teleseismic traveltime tomography,better tomography results can be achieved by a two-step inversion method.(2)Global mantle heterogeneities can cause large traveltime residuals(up to about 0.55 s),which leads to evident imaging artifacts.(3)The tomographic accuracy and resolution of M1 decrease with increasing station spacing when measuring the relative traveltime difference between two adjacent stations.(4)The traveltime anomalies caused by the source uncertainties are generally less than 0.2 s,and the impact of source uncertainties is negligible.

Spacecraft potential variations of the Swarm satellites at low Earth orbital altitudes

In this study, we provide the first detailed analysis of variations in the spacecraft potential (Vs) of the three Swarm satellites, which are flying at about 400-500 km. Unlike previous studies that have investigated extreme charging events, usually with spacecraft potentials as negative as −100 V, this study is focused on variations of Swarm Vs readings, which fall within a few negative volts. The Swarm observations show that spacecraft at low Earth orbital (LEO) altitudes are charged only slightly negatively, varying between −7 V and 0 V, with the majority of recorded potentials at these altitudes clustering close to −2 V. However, a second peak of Vs data is found at −5.5 V, though the event numbers for these more-negative observations are less, by an order of magnitude, than for incidents near the −2 V peak. These two distinct Vs peaks suggest two different causes. We have thus divided the Swarm spacecraft Vs data into two categories: less-negatively charged (−5 < Vs < 0 V) and more-negatively-charged (−6.5 < Vs < −5 V). These two Vs categories exhibit different spatial and temporal distributions. The Vs observations in the first category remain relatively closer to 0 V above the magnetic equator, but become much more negative at low and middle latitudes on the day side;at high latitudes, these first-category Vs readings are relatively more-negative during local summer. Second-category Vs events cluster into two bands at the middle latitudes (between ±20°-50° magnetic latitude), but with slightly more negative readings at the South Atlantic Anomaly (SAA) region;at high latitudes, these rarer but more-negative second-category Vs events exhibit relatively more-negative values during local winter, which is opposite to the seasonal pattern seen in the first category. By comparing Vs data to the distributions of background plasma density at Swarm altitudes, we find for the first category that more-negative Vs readings are recorded at regions with higher background plasma density, while for the second category the more-negative Vs data are observed at regions with lower background plasma density. This can be explained as follows: the electron and ion fluxes incident on Swarm surface, whose differences determine the potential of Swarm, are dominated by the background “cold” plasma (due to ionization) and “hot” plasma (due to precipitated particles from magnetosphere) for the two Vs categories, respectively.

Landslide Research from the Perspectives of Qinling Mountains in China:A Critical Review

Landslides pose a frequent geological threat,endangering both productivity and the wellbeing of human life and property.In recent years,landslides have received widespread attention in various fields.This article presents a comprehensive review of landslide research in the Qinling Mountains,China.The first part introduces landslide investigation and inventory,which include manual visual interpretation and automatic landslide extraction.The second part discusses the types,characteristics,and temporal-spatial distribution of landslides in the Qinling Mountains.In the third part,the mechanisms and stability analysis of landslides are explored,along with a discussion of the applicability of various simulation methods.The fourth part focuses on significant studies related to landslide evaluation,including susceptibility,hazard,and risk assessment.The fifth part addresses landslide monitoring and early warning systems.Finally,an assessment is made of the current issues and research status concerning landslide studies in the Qinling Mountains,followed by a discussion on future research directions.

Ionospheric TEC and plasma anomalies possibly associated with the 14 July 2019 M_(w) 7.2 Indonesia Laiwui earthquake,from analysis of GPS and CSES data

This study presents signatures of seismo-ionospheric perturbations possibly related to the 14 July 2019 M_(w)7.2 Laiwui earthquake,detected by a cross-validation analysis of total electron content(TEC)data of the global ionospheric map(GIM)from GPS and plasma parameter data recorded by the China Seismo-Electromagnetic Satellite(CSES).After separating pre-seismic ionospheric phenomena from the ionospheric disturbances due to the magnetospheric and solar activities,we have identified three positive temporal anomalies,around the epicenter,at 1 day,3 days and 8 days before the earthquake(14 July 2019),along with a negative anomaly 6 days after the earthquake.These results agree well with the TEC spatial variations in latitude-longitude-time(LLT)maps.To confirm these anomalies further,we employed the moving mean method(MMM)to analyze ionospheric plasma parameters(electron,O^(+) and He^(+) densities)recorded by the Langmuir probe(LAP)and Plasma Analyzer Package(PAP)onboard the CSES.The analysis detected on,on Day Two,Day Four,and Day Seven before the earthquake,remarkable enhancements along the orbits around when in proximity to the epicenter.To make the investigations still more convincing,we compared the orbits on which anomalous readings were recorded to their corresponding four nearest revisiting orbits;the comparison did indeed indicate the existence of plasma parameter anomalies that appear to be associated with the Laiwui earthquake.All these results ilustrate that the unusual ionospheric perturbations detected through GPS and CSES data are possibly associated with the M_(w)7.2 Laiwui earthquake,which suggests that at least some earthquakes may be predicted by alertness to pre-seismic ionospheric anomalies over regions known to be at seismic risk.This case study also contributes additional information of value to our understanding of lithosphere-atmosphere-ionosphere coupling.

Quantifying the Spatial Characteristics of the Moisture Transport Affecting Precipitation Seasonality and Recycling Variability in Central Asia

Moisture contribution and transport pathways for Central Asia(CA)are quantitatively examined using the Lagrangian water cycle model based on reanalysis and observational data to explain the precipitation seasonality and the moisture transport variation during 1979-2015.Westerly-related(northwesterly and westerly)transport explains 42%of CA precipitation and dominates in southwest CA,where precipitation is greatest in the cold season.Southeast CA,including part of Northwest China,experiences its maximum precipitation in the warm season and is solely dominated by southerly transport,which explains about 48%of CA precipitation.The remaining 10%of CA precipitation is explained by northerly transport,which steadily impacts north CA and causes a maximum in precipitation in the warm season.Most CA areas are exposed to seasonally varying moisture transport,except for southeast and north CA,which are impacted by southerly and northerly transport year-round.In general,the midlatitude westerlies-driven transport and the Indian monsoon-driven southerly-related transport explain most of the spatial differences in precipitation seasonality over CA.Moreover,the contribution ratio of local evaporation in CA to precipitation exhibits significant interdecadal variability and a meridionally oriented tripole of moisture transport anomalies.Since the early 2000s,CA has experienced a decade of anomalously low local moisture contribution,which seems jointly determined by the weakened moisture contribution from midlatitudes(the Atlantic,Europe,and CA itself)and the enhanced contribution from high latitudes(West Siberia and the Arctic)and tropical areas(South Asia and the Indian Ocean).

Progress of International Meridian Circle Program

Based on the Chinese Meridian Project(CMP),the International Meridian Circle Program(IMCP)aims to coordinate the deployment of a comprehensive ground-based monitoring network along the 120°E-60°W Great Meridian Circle to track the propagation and evolution of space weather events from the Sun to the Earth,as well as the imprints of other major natural and anthropic hazards on the ionosphere,the middle and upper atmosphere.Currently,we have completed the IMCP headquarters building in Beijing and established the China-Brazil Joint Laboratory for Space Weather in cooperation with Brazil.Meanwhile,the Chinese Meridian Project PhaseⅡand different components of the IMCP observation system are under construction.

New Exploration of Tracking Deep Ancient Crustal Components: A Combined Analysis of Xenocrystic/Inherited Zircon Information within Different Genetic Types of Granitoids in Chinese Altai

Revealing deep composition information is crucial for systematic understanding of continental crust architecture.Deep exploration has become an important trend in the development of geoscience,and using magmatic rocks and their deep-source rock inclusions as‘rock probes’to trace the earth’s deep material information has been an effective way in recent years(e.g.,Mo,2011).

Contact vibration analysis of the functionally graded material coated half-space under a rigid spherical punch

This paper studies the contact vibration problem of an elastic half-space coated with functionally graded materials(FGMs)subject to a rigid spherical punch.A static force superimposing a dynamic time-harmonic force acts on the rigid spherical punch.Firstly,we give the static contact problem of FGMs by a least-square fitting approach.Next,the dynamic contact pressure is solved by employing the perturbation method.Lastly,the dynamic contact stiffness with different dynamic contact displacement conditions is derived for the FGM coated half-space.The effects of the gradient index,coating thickness,internal friction,and punch radius on the dynamic contact stiffness factor are discussed in detail.

Calculation of landslide occurrence probability in Taiwan region under different ground motion conditions

In this study,Bayesian probability method and machine learning model are used to study the real occurrence probability of earthquake-induced landslide risk in Taiwan region.The analyses were based on the 1999 Taiwan Chi-Chi Earthquake,the largest earthquake in the history in this Region in a hundred years,thus can provide better control on the prediction accuracy of the model.This seismic event has detailed and complete seismic landslide inventories identified by polygons,including 9272 seismic landslide records.Taking into account the real earthquake landslide occurrence area,the difference in landslide area and the non-sliding/sliding sample ratios and other factors,a total of 13,656,000 model training samples were selected.We also considered other seismic landslide influencing factors,including elevation,slope,aspect,topographic wetness index,lithology,distance to fault,peak ground acceleration and rainfall.Bayesian probability method and machine learning model were combined to establish the multi-factor influence of earthquake landslide occurrence model.The model is then applied to the whole Taiwan region using different ground motion peak accelerations(from 0.1 g to 1.0 g with 0.1 g intervals)as a triggering factor to complete the real probability of earthquake landslide map in Taiwan under different peak ground accelerations,and the functional relationship between different Peak Ground Acceleration and their predicted area is obtained.