{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T19:25:15Z","timestamp":1773257115486,"version":"3.50.1"},"reference-count":89,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,8,29]],"date-time":"2022-08-29T00:00:00Z","timestamp":1661731200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China","award":["ZDJ2020-10"],"award-info":[{"award-number":["ZDJ2020-10"]}]},{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China","award":["ZDJ2021-12"],"award-info":[{"award-number":["ZDJ2021-12"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Rainfall-induced landslides pose a significant threat to the lives and property of residents in the southeast mountainous and hilly area; hence, characterizing the distribution pattern and effective susceptibility mapping for rainfall-induced landslides are regarded as important and necessary measures to remediate the damage and loss resulting from landslides. From 10 June 2019 to 13 June 2019, continuous heavy rainfall occurred in Longchuan County, Guangdong Province; this event triggered extensive landslide disasters in the villages of Longchuan County. Based on high-resolution satellite images, a landslide inventory of the affected area was compiled, comprising a total of 667 rainfall-induced landslides over an area of 108 km2. These landslides consisted of a large number of shallow landslides with a few flowslides, rockfalls, and debris flows, and the majority of them occurred in Mibei and Yanhua villages. The inventory was used 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 slope angle, TWI, and road density. The landslide area density (LAD) increased with the increase in the above three influencing factors and was described by an exponential or linear relationship. In addition, southeast and south aspect hillslopes were more prone to collapse than the northwest\u00ad\u2013north aspect ones because of the influence of the summer southeast monsoon. A new open-source tool named MAT.TRIGRS(V1.0) was adopted to establish the landslide susceptibility map in landslide abundance areas and to back-analyze the response of the rainfall process to the change in landslide stability. The prediction results were roughly consistent with the actual landslide distribution, and most areas with high susceptibility were located on both sides of the river valley; that is, the areas with relatively steep slopes. The slope stability changes in different periods revealed that the onset of heavy rain on 10 June 2019 was the main triggering factor of these group\u2011occurring landslides, and the subsequent rainfall with low intensity had little impact on slope stability.<\/jats:p>","DOI":"10.3390\/rs14174257","type":"journal-article","created":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T01:37:55Z","timestamp":1661823475000},"page":"4257","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["Characterizing the Distribution Pattern and a Physically Based Susceptibility Assessment of Shallow Landslides Triggered by the 2019 Heavy Rainfall Event in Longchuan County, Guangdong Province, China"],"prefix":"10.3390","volume":"14","author":[{"given":"Siyuan","family":"Ma","sequence":"first","affiliation":[{"name":"Institute of Geology, China Earthquake Administration, Beijing 100029, China"},{"name":"Key Laboratory of Seismic and Volcanic Hazards, Institute of Geology, China Earthquake Administration, Beijing 100029, China"}]},{"given":"Xiaoyi","family":"Shao","sequence":"additional","affiliation":[{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China"},{"name":"Key Laboratory of Compound and Chained Natural Hazards Dynamics, Ministry of Emergency Management of China, Beijing 100085, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3956-4925","authenticated-orcid":false,"given":"Chong","family":"Xu","sequence":"additional","affiliation":[{"name":"National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China"},{"name":"Key Laboratory of Compound and Chained Natural Hazards Dynamics, Ministry of Emergency Management of China, Beijing 100085, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e2019GL085347","DOI":"10.1029\/2019GL085347","article-title":"Changes in Extreme Precipitation and Landslides Over High Mountain Asia","volume":"47","author":"Kirschbaum","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2262","DOI":"10.1038\/s41467-021-22398-4","article-title":"Global connections between El Nino and landslide impacts","volume":"12","author":"Emberson","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1130\/G33217.1","article-title":"Global patterns of loss of life from landslides","volume":"40","author":"Petley","year":"2012","journal-title":"Geology"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2357","DOI":"10.1007\/s10346-018-1037-6","article-title":"Spatial and temporal analysis of a fatal landslide inventory in China from 1950 to 2016","volume":"15","author":"Lin","year":"2018","journal-title":"Landslides"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.earscirev.2016.08.011","article-title":"Landslides in a changing climate","volume":"162","author":"Gariano","year":"2016","journal-title":"Earth Sci. Rev."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.nhres.2022.02.001","article-title":"Bibliometric analysis of landslide research based on the WOS database","volume":"2","author":"Huang","year":"2022","journal-title":"Nat. Hazards Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"e2021GL095850","DOI":"10.1029\/2021GL095850","article-title":"Coseismic Debris Remains in the Orogen Despite a Decade of Enhanced Landsliding","volume":"48","author":"Dai","year":"2021","journal-title":"Geophys. Res. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"e2020GL090509","DOI":"10.1029\/2020GL090509","article-title":"Rapidly Evolving Controls of Landslides After a Strong Earthquake and Implications for Hazard Assessments","volume":"48","author":"Fan","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1029\/2018RG000626","article-title":"Earthquake-induced chains of geologic hazards: Patterns, mechanisms, and impacts","volume":"57","author":"Fan","year":"2019","journal-title":"Rev. Geophys."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Schmitt, R., Tanyas, H., Jessee, A., Zhu, J., Biegel, K., Allstadt, K., Jibson, R., Thompson, E., Westen, C.J., and Sato, H. (2017). An Open Repository of Earthquake-Triggered Ground-Failure Inventories.","DOI":"10.3133\/ds1064"},{"key":"ref_11","first-page":"583","article-title":"Earthquake-Triggered Landslides","volume":"2","author":"Tian","year":"2021","journal-title":"Treatise Geomorphol."},{"key":"ref_12","first-page":"1122","article-title":"Probability of coseimic landslides: A new generation of earthquake-triggered landslide hazard model","volume":"27","author":"Xu","year":"2019","journal-title":"J. Eng. Geol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Shao, X., and Xu, C. (2022). Earthquake-induced landslides susceptibility assessment: A review of the state-of-the-art. Nat. Hazards Res., in press.","DOI":"10.1016\/j.nhres.2022.03.002"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1002\/2017EF000715","article-title":"Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness","volume":"6","author":"Kirschbaum","year":"2018","journal-title":"Earths Future"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.5194\/nhess-22-1129-2022","article-title":"Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories","volume":"22","author":"Emberson","year":"2022","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"903","DOI":"10.5194\/esurf-6-903-2018","article-title":"Initial insights from a global database of rainfall-induced landslide inventories: The weak influence of slope and strong influence of total storm rainfall","volume":"6","author":"Marc","year":"2018","journal-title":"Earth Surf. Dyn."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1957","DOI":"10.1007\/s10346-022-01904-9","article-title":"Spatial\u2013temporal distribution and failure mechanism of group-occurring landslides in Mibei village, Longchuan County, Guangdong, China","volume":"19","author":"Feng","year":"2022","journal-title":"Landslides"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.geomorph.2015.05.016","article-title":"Rainfall intensity\u2013duration thresholds for the initiation of landslides in Zhejiang Province, China","volume":"245","author":"Ma","year":"2015","journal-title":"Geomorphology"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.geomorph.2006.01.002","article-title":"Recent rainfall-induced landslides and debris flow in northern Taiwan","volume":"77","author":"Chen","year":"2006","journal-title":"Geomorphology"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"103225","DOI":"10.1016\/j.earscirev.2020.103225","article-title":"Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance","volume":"207","author":"Merghadi","year":"2020","journal-title":"Earth Sci. Rev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.earscirev.2018.03.001","article-title":"A review of statistically-based landslide susceptibility models","volume":"180","author":"Reichenbach","year":"2018","journal-title":"Earth Sci. Rev."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1016\/j.catena.2015.05.019","article-title":"Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines","volume":"133","author":"Hong","year":"2015","journal-title":"Catena"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Shao, X., Ma, S., Xu, C., Zhang, P., Wen, B., Tian, Y., Zhou, Q., and Cui, Y. (2019). Planet Image-Based Inventorying and Machine Learning-Based Susceptibility Mapping for the Landslides Triggered by the 2018 Mw6.6 Tomakomai, Japan Earthquake. Remote Sens., 11.","DOI":"10.3390\/rs11080978"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"107222","DOI":"10.1016\/j.geomorph.2020.107222","article-title":"Effects of sampling intensity and non-slide\/slide sample ratio on the occurrence probability of coseismic landslides","volume":"363","author":"Shao","year":"2020","journal-title":"Geomorphology"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"105355","DOI":"10.1016\/j.catena.2021.105355","article-title":"Landslide susceptibility analyses using Random Forest, C4.5, and C5.0 with balanced and unbalanced datasets","volume":"203","author":"Tanyu","year":"2021","journal-title":"CATENA"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1007\/s11069-014-1506-8","article-title":"An assessment of multivariate and bivariate approaches in landslide susceptibility mapping: A case study of Duzkoy district","volume":"76","author":"Kavzoglu","year":"2015","journal-title":"Nat. Hazards"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1016\/j.scitotenv.2019.02.263","article-title":"Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China","volume":"666","author":"Wang","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/j.cageo.2012.01.002","article-title":"Comparison of different models for susceptibility mapping of earthquake triggered landslides related with the 2008 Wenchuan earthquake in China","volume":"46","author":"Xu","year":"2012","journal-title":"Comput. Geosci."},{"key":"ref_29","first-page":"1","article-title":"Decision tree based ensemble machine learning approaches for landslide susceptibility mapping","volume":"37","author":"Arabameri","year":"2021","journal-title":"Geocarto Int."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Adnan, M.S.G., Rahman, M.S., Ahmed, N., Ahmed, B., Rabbi, M.F., and Rahman, R.M. (2020). Improving Spatial Agreement in Machine Learning-Based Landslide Susceptibility Mapping. Remote Sens., 12.","DOI":"10.3390\/rs12203347"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.geomorph.2009.06.020","article-title":"Optimal landslide susceptibility zonation based on multiple forecasts","volume":"114","author":"Rossi","year":"2010","journal-title":"Geomorphology"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"101362","DOI":"10.1016\/j.ijdrr.2019.101362","article-title":"Spatial prediction strategy for landslides triggered by large earthquakes oriented to emergency response, mid-term resettlement and later reconstruction","volume":"43","author":"Ma","year":"2020","journal-title":"Int. J. Disaster Risk Reduct."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"107121","DOI":"10.1016\/j.geomorph.2020.107121","article-title":"A GIS-physically-based emergency methodology for predicting rainfall-induced shallow landslide zonation","volume":"359","year":"2020","journal-title":"Geomorphology"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"L22402","DOI":"10.1029\/2006GL028010","article-title":"Evaluation of the potential of NASA multi-satellite precipitation analysis in global landslide hazard assessment","volume":"33","author":"Hong","year":"2006","journal-title":"Geophys. Res. Lett."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"101248","DOI":"10.1016\/j.gsf.2021.101248","article-title":"National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data","volume":"12","author":"Lin","year":"2021","journal-title":"Geosci. Front."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1897","DOI":"10.1029\/2000WR900090","article-title":"Landslide triggering by rain infiltration","volume":"36","author":"Iverson","year":"2000","journal-title":"Water Resour. Res."},{"key":"ref_37","first-page":"209","article-title":"Recommendations for the quantitative analysis of landslide risk","volume":"73","author":"Corominas","year":"2014","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Fell, R., Corominas, J., Bonnard, C., Cascini, L., Leroi, E., and Savage, W. (2008). Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Eng. Geol., 102.","DOI":"10.1016\/j.enggeo.2008.03.014"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1007\/s11069-009-9431-y","article-title":"Susceptibility analysis of shallow landslides source areas using physically based models","volume":"53","author":"Sorbino","year":"2010","journal-title":"Nat. Hazards"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Baum, R.L., Savage, W.Z., and Godt, J.W. (2008). TRIGRS-A Fortran Program for Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis, Version 2.0.","DOI":"10.3133\/ofr20081159"},{"key":"ref_41","first-page":"F03013","article-title":"Estimating the timing and location of shallow rainfall-induced landslides using a model for transient, unsaturated infiltration","volume":"115","author":"Baum","year":"2010","journal-title":"J. Geophys. Res. F Earth Surf."},{"key":"ref_42","first-page":"249","article-title":"Preparing first-time slope failures hazard maps: From pixel-based to slope unit-based","volume":"17","author":"Alvioli","year":"2019","journal-title":"Landslides"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.scitotenv.2016.06.124","article-title":"Prediction of shallow landslide occurrence: Validation of a physically-based approach through a real case study","volume":"569-570","author":"Schiliro","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.catena.2016.02.009","article-title":"Deterministic approach for susceptibility assessment of shallow debris slide in the Darjeeling Himalayas, India","volume":"142","author":"Sarkar","year":"2016","journal-title":"Catena"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.envsoft.2016.08.009","article-title":"Development of time-variant landslide-prediction software considering three-dimensional subsurface unsaturated flow","volume":"85","author":"An","year":"2016","journal-title":"Environ. Model. Softw."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s10346-009-0154-7","article-title":"Rainfall-induced shallow landslides: A model for the triggering mechanism of some case studies in Northern Italy","volume":"6","author":"Montrasio","year":"2009","journal-title":"Landslides"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1007\/s11069-014-1239-8","article-title":"A prototype system for space\u2013time assessment of rainfall-induced shallow landslides in Italy","volume":"74","author":"Montrasio","year":"2014","journal-title":"Nat. Hazards"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2331","DOI":"10.1007\/s10706-018-0465-3","article-title":"Soil Saturation and Stability Analysis of a Test Site Slope Using the Shallow Landslide Instability Prediction (SLIP) Model","volume":"36","author":"Montrasio","year":"2018","journal-title":"Geotech. Geol. Eng."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1007\/s12665-017-6635-4","article-title":"Comparing the performance of TRIGRS and TiVaSS in spatial and temporal prediction of rainfall-induced shallow landslides","volume":"76","author":"Tran","year":"2017","journal-title":"Environ. Earth Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1016\/j.gsf.2020.09.008","article-title":"A GIS Tool for Infinite Slope Stability Analysis (GIS-TISSA)","volume":"12","author":"Sanders","year":"2021","journal-title":"Geosci. Front."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.jhydrol.2016.10.016","article-title":"Development of a coupled hydrological-geotechnical framework for rainfall-induced landslides prediction","volume":"543","author":"He","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"5035","DOI":"10.5194\/hess-20-5035-2016","article-title":"iCRESTRIGRS: A coupled modeling system for cascading flood\u2013landslide disaster forecasting","volume":"20","author":"Zhang","year":"2016","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"151","DOI":"10.5194\/nhess-13-151-2013","article-title":"HIRESSS: A physically based slope stability simulator for HPC applications","volume":"13","author":"Rossi","year":"2013","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1007\/s10346-017-0809-8","article-title":"Soil characterization for shallow landslides modeling: A case study in the Northern Apennines (Central Italy)","volume":"14","author":"Tofani","year":"2017","journal-title":"Landslides"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1919","DOI":"10.5194\/nhess-18-1919-2018","article-title":"Application of a physically based model to forecast shallow landslides at a regional scale","volume":"18","author":"Salvatici","year":"2018","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1731","DOI":"10.1007\/s10346-017-0812-0","article-title":"A probabilistic model for rainfall\u2014induced shallow landslide prediction at the regional scale","volume":"14","author":"Salciarini","year":"2017","journal-title":"Landslides"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2833","DOI":"10.5194\/nhess-13-2833-2013","article-title":"Landslide and debris flow susceptibility zonation using TRIGRS for the 2011 Seoul landslide event","volume":"13","author":"Park","year":"2013","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1007\/s11069-010-9670-y","article-title":"Evaluation of TRIGRS (transient rainfall infiltration and grid-based regional slope-stability analysis)\u2019s predictive skill for hurricane-triggered landslides: A case study in Macon County, North Carolina","volume":"58","author":"Liao","year":"2011","journal-title":"Natural Hazards"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1007\/s10346-015-0646-6","article-title":"Assessment of shallow landslide susceptibility using the transient infiltration flow model and GIS-based probabilistic approach","volume":"13","author":"Lee","year":"2015","journal-title":"Landslides"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1007\/s11069-016-2729-7","article-title":"Basinwide disaster loss assessments under extreme climate scenarios: A case study of the Kaoping River basin","volume":"86","author":"Li","year":"2016","journal-title":"Nat. Hazards"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1002\/esp.4050","article-title":"Prediction of rainfall-induced shallow landslides in the Loess Plateau, Yan\u2019an, China, using the TRIGRS model","volume":"42","author":"Zhuang","year":"2016","journal-title":"Earth Surf. Processes Landf."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"An, K., Kim, S., Chae, T., and Park, D. (2018). Developing an Accessible Landslide Susceptibility Model Using Open-Source Resources. Sustainability, 10.","DOI":"10.3390\/su10020293"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Hsu, Y.-C., and Liu, K.-F. (2019). Combining TRIGRS and DEBRIS-2D Models for the Simulation of a Rainfall Infiltration Induced Shallow Landslide and Subsequent Debris Flow. Water, 11.","DOI":"10.3390\/w11050890"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1007\/s12665-016-5326-x","article-title":"Regional modeling of rainfall-induced landslides using TRIGRS model by incorporating plant cover effects: Case study in Hulu Kelang, Malaysia","volume":"75","author":"Saadatkhah","year":"2016","journal-title":"Environ. Earth Sci."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.scib.2019.03.002","article-title":"Stable classification with limited sample: Transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017","volume":"64","author":"Gong","year":"2019","journal-title":"Sci. Bull."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1007\/s10346-009-0147-6","article-title":"Interpretation of earthquake-induced landslides triggered by the 12 May 2008, M7.9 Wenchuan earthquake in the Beichuan area, Sichuan Province, China using satellite imagery and Google Earth","volume":"6","author":"Sato","year":"2009","journal-title":"Landslides"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.1007\/s10346-020-01366-x","article-title":"Landslide development within 3 years after the 2015 Mw 7.8 Gorkha earthquake, Nepal","volume":"17","author":"Tian","year":"2020","journal-title":"Landslides"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"2343","DOI":"10.1007\/s10346-018-1044-7","article-title":"Regional-scale back-analysis using TRIGRS: An approach to advance landslide hazard modeling and prediction in sparse data regions","volume":"15","author":"Weidner","year":"2018","journal-title":"Landslides"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1007\/s10346-017-0931-7","article-title":"Three-dimensional, time-dependent modeling of rainfall-induced landslides over a digital landscape: A case study","volume":"15","author":"Tran","year":"2018","journal-title":"Landslides"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.envsoft.2016.04.002","article-title":"Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface","volume":"81","author":"Alvioli","year":"2016","journal-title":"Environ. Model. Softw."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/j.enggeo.2008.03.019","article-title":"Transient deterministic shallow landslide modeling: Requirements for susceptibility and hazard assessments in a GIS framework","volume":"102","author":"Godt","year":"2008","journal-title":"Eng. Geol."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.nhres.2021.11.001","article-title":"MAT.TRIGRS (V1.0): A new open-source tool for predicting spatiotemporal distribution of rainfall-induced landslides","volume":"1","author":"Ma","year":"2021","journal-title":"Nat. Hazards Res."},{"key":"ref_73","first-page":"67","article-title":"Shallow landslide hazard map of Seattle, Washington","volume":"20","author":"Harp","year":"2008","journal-title":"Rev. Eng. Geol."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"2421","DOI":"10.5194\/nhess-19-2421-2019","article-title":"Mapping the susceptibility of rain-triggered lahars at Vulcano island (Italy) combining field characterization, geotechnical analysis, and numerical modelling","volume":"19","author":"Baumann","year":"2019","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1007\/s12665-018-7436-0","article-title":"Assessing shallow landslide hazards using the TRIGRS and SHALSTAB models, Serra do Mar, Brazil","volume":"77","author":"Vieira","year":"2018","journal-title":"Environ. Earth Sci."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/S0022-1694(97)00059-0","article-title":"Including spatially variable soil depths in TOPMODEL","volume":"202","author":"Saulnier","year":"1997","journal-title":"J. Hydrol."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"3181","DOI":"10.1007\/s11069-021-04819-1","article-title":"Group-occurring landslides and debris flows caused by the continuous heavy rainfall in June 2019 in Mibei Village, Longchuan County, Guangdong Province, China","volume":"108","author":"Bai","year":"2021","journal-title":"Nat. Hazards"},{"key":"ref_78","unstructured":"Das, B. (2008). Advanced Soil Mechanics, Taylor & Francis."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"104999","DOI":"10.1016\/j.catena.2020.104999","article-title":"Prediction of spatiotemporal stability and rainfall threshold of shallow landslides using the TRIGRS and Scoops3D models","volume":"197","author":"He","year":"2021","journal-title":"Catena"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"105213","DOI":"10.1016\/j.catena.2021.105213","article-title":"Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale","volume":"201","author":"Medina","year":"2021","journal-title":"Catena"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"2894","DOI":"10.1175\/JAS-D-12-0340.1","article-title":"Distribution and Mechanisms of Orographic Precipitation Associated with Typhoon Morakot (2009)","volume":"70","author":"Yu","year":"2013","journal-title":"J. Atmos. Sci."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"2571","DOI":"10.3390\/rs5062571","article-title":"Topographic Correction of Wind-Driven Rainfall for Landslide Analysis in Central Taiwan with Validation from Aerial and Satellite Optical Images","volume":"5","author":"Liu","year":"2013","journal-title":"Remote Sens."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"1661","DOI":"10.1002\/esp.4601","article-title":"Controls of preferential orientation of earthquake- and rainfall-triggered landslides in Taiwan\u2019s orogenic mountain belt","volume":"44","author":"Chen","year":"2019","journal-title":"Earth Surf. Processes Landf."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.ecolmodel.2011.12.007","article-title":"How can statistical models help to determine driving factors of landslides?","volume":"239","author":"Vorpahl","year":"2012","journal-title":"Ecol. Model."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1007\/s10346-013-0391-7","article-title":"Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression","volume":"11","author":"Kavzoglu","year":"2014","journal-title":"Landslides"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.enggeo.2017.03.015","article-title":"Anthropogenically induced landslides\u2013A challenge for railway infrastructure in mountainous regions","volume":"222","author":"Laimer","year":"2017","journal-title":"Eng. Geol."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.apgeog.2018.03.003","article-title":"Land use changes, landslides and roads in the Phewa Watershed, Western Nepal from 1979 to 2016","volume":"94","author":"Vuillez","year":"2018","journal-title":"Appl. Geogr."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"2115","DOI":"10.1007\/s11069-020-04264-6","article-title":"Influence of human activity on landslide susceptibility development in the Three Gorges area","volume":"104","author":"Li","year":"2020","journal-title":"Nat. Hazards"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1007\/s11069-021-05199-2","article-title":"Could road constructions be more hazardous than an earthquake in terms of mass movement?","volume":"112","author":"Kirschbaum","year":"2022","journal-title":"Nat. Hazards"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/17\/4257\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:19:44Z","timestamp":1760141984000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/17\/4257"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,29]]},"references-count":89,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["rs14174257"],"URL":"https:\/\/doi.org\/10.3390\/rs14174257","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,29]]}}}