{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T03:44:48Z","timestamp":1775619888962,"version":"3.50.1"},"reference-count":74,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,5,7]],"date-time":"2021-05-07T00:00:00Z","timestamp":1620345600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2018YFC1504704"],"award-info":[{"award-number":["2018YFC1504704"]}]},{"name":"Science and Technology Major Project of Gansu Province","award":["19ZD2FA002"],"award-info":[{"award-number":["19ZD2FA002"]}]},{"name":"Program for International S&amp;T Cooperation Projects of Gansu Province","award":["2018-0204-GJC-0043"],"award-info":[{"award-number":["2018-0204-GJC-0043"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["lzujbky-2018-46"],"award-info":[{"award-number":["lzujbky-2018-46"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Groups of landslides induced by heavy rainfall are widely distributed on a global basis and they usually result in major losses of human life and economic damage. However, compared with landslides induced by earthquakes, inventories of landslides induced by heavy rainfall are much less common. In this study we used high-precision remote sensing images before and after continuous heavy rainfall in southern Tianshui, China, from 20 June to 25 July 2013, to produce an inventory of 14,397 shallow landslides. Based on the results of landslide inventory, we utilized machine learning and the geographic information system (GIS) to map landslide susceptibility in this area and evaluated the relative weight of various factors affecting landslide development. First, 18 variables related to geomorphic conditions, slope material, geological conditions, and human activities were selected through collinearity analysis; second, 21 selected machine learning models were trained and optimized in the Python environment to evaluate the susceptibility of landslides. The results showed that the ExtraTrees model was the most effective for landslide susceptibility assessment, with an accuracy of 0.91. This predictive ability means that our landslide susceptibility results can be used in the implementation of landslide prevention and mitigation measures in the region. Analysis of the importance of the factors showed that the contribution of slope aspect (SA) was significantly higher than that of the other factors, followed by planar curvature (PLC), distance to river (DR), distance to fault (DTF), normalized difference vehicle index (NDVI), distance to road (DTR), and other factors. We conclude that factors related to geomorphic conditions are principally responsible for controlling landslide susceptibility in the study area.<\/jats:p>","DOI":"10.3390\/rs13091819","type":"journal-article","created":{"date-parts":[[2021,5,7]],"date-time":"2021-05-07T22:36:24Z","timestamp":1620426984000},"page":"1819","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["AI-Based Susceptibility Analysis of Shallow Landslides Induced by Heavy Rainfall in Tianshui, China"],"prefix":"10.3390","volume":"13","author":[{"given":"Tianjun","family":"Qi","sequence":"first","affiliation":[{"name":"MOE Key Laboratory of Western China\u2019s Environmental Systems, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1180-8868","authenticated-orcid":false,"given":"Yan","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Earth Sciences, Lanzhou University, Lanzhou 730000, China"}]},{"given":"Xingmin","family":"Meng","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Western China\u2019s Environmental Systems, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China"},{"name":"School of Earth Sciences, Lanzhou University, Lanzhou 730000, China"}]},{"given":"Guan","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Earth Sciences, Lanzhou University, Lanzhou 730000, China"}]},{"given":"Tom","family":"Dijkstra","sequence":"additional","affiliation":[{"name":"School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough LE11 3TU, UK"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1130\/0016-7606(1984)95<406:LCBE>2.0.CO;2","article-title":"Landslides caused by earthquakes","volume":"95","author":"Keefer","year":"1984","journal-title":"Geol. Soc. Am. Bull."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.enggeo.2004.01.006","article-title":"Landslides triggered by the 23 November 2000 rainfall event in the Imperia Province, Western Liguria, Italy","volume":"73","author":"Guzzetti","year":"2004","journal-title":"Eng. Geol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1007\/s10346-007-0093-0","article-title":"Comparison between the two triggered landslides in mid-Niigata, Japan by July 13 heavy rainfall and October 23 intensive earthquakes in 2004","volume":"4","author":"Yamagishi","year":"2007","journal-title":"Landslides"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.geomorph.2007.04.007","article-title":"Landslides triggered by the 8 October 2005 Kashmir Earthquake","volume":"94","author":"Owen","year":"2008","journal-title":"Geomorphology"},{"key":"ref_5","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_6","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1007\/s10346-011-0268-6","article-title":"Rainfall-induced landslide event of May 2010 in the eastern part of the Czech Republic","volume":"8","author":"Klime","year":"2011","journal-title":"Landslides"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1923","DOI":"10.1126\/science.260.5116.1923","article-title":"Spatiotemporal patterns in the energy release of great earthquakes","volume":"260","author":"Romanowicz","year":"1993","journal-title":"Science"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Kirschbaum, D. (2014). Global Catalog of Rainfall-Triggered Landslides for Spatial and Temporal Hazard Characterization. Landslide Science for a Safer Geoenvironment, Springer.","DOI":"10.1007\/978-3-319-05050-8_125"},{"key":"ref_9","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":"Guzzetti","year":"2016","journal-title":"Earth Sci. Rev."},{"key":"ref_10","first-page":"1","article-title":"Evaluation of the potential of NASA multi-satellite precipitation analysis in global landslide hazard assessment","volume":"33","author":"Hong","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_11","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_12","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s11069-020-03913-0","article-title":"Rainfall-induced landslides forecast using local precipitation and global climate indexes","volume":"102","author":"Fustos","year":"2020","journal-title":"Nat. Hazards"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"4817","DOI":"10.1080\/014311601131000082424","article-title":"Characterization of rainfall-induced landslides","volume":"24","author":"Dai","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","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_15","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1016\/j.geomorph.2005.06.002","article-title":"Probabilistic landslide hazard assessment at the basin scale","volume":"72","author":"Guzzetti","year":"2005","journal-title":"Geomorphology"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1007\/s10064-009-0204-3","article-title":"High-resolution lidar-based landslide hazard mapping and modeling, UCSF Parnassus Campus, San Francisco, USA","volume":"68","author":"Haneberg","year":"2009","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1038\/ngeo1479","article-title":"Landslide erosion coupled to tectonics and river incision","volume":"5","author":"Larsen","year":"2012","journal-title":"Nat. Geosci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.earscirev.2012.02.001","article-title":"Landslide inventory maps: New tools for an old problem","volume":"112","author":"Guzzetti","year":"2012","journal-title":"Earth Sci. Rev."},{"key":"ref_19","first-page":"900","article-title":"Factors controlling landslide frequency-area distributions","volume":"44","author":"Westen","year":"2018","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.geomorph.2005.07.006","article-title":"Analysis of LiDAR-derived topographic information for characterizing and differentiating landslide morphology and activity","volume":"73","author":"Glenn","year":"2006","journal-title":"Geomorphology"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2539","DOI":"10.5194\/nhess-10-2539-2010","article-title":"Remote landslide mapping using a laser rangefinder binocular and GPS","volume":"10","author":"Santangelo","year":"2010","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_22","first-page":"1","article-title":"Large landslides and deep-seated gravitational slope deformations in the Czech Flysch Carpathians: New LiDAR-based inventory","volume":"346","author":"Lenart","year":"2019","journal-title":"Geomorphology"},{"key":"ref_23","first-page":"433","article-title":"Large-scale landslide and their sliding mechanisms in China since the 20th Century","volume":"26","author":"Huang","year":"2007","journal-title":"Chin. J. Rock Mech. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1007\/s10346-003-0006-9","article-title":"Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area of Agano River, Niigata Prefecture, Japan","volume":"1","author":"Ayalew","year":"2004","journal-title":"Landslides"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1016\/j.geomorph.2006.10.036","article-title":"Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of Turkey)","volume":"94","author":"Nefeslioglu","year":"2008","journal-title":"Geomorphology"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.1002\/esp.263","article-title":"Assessment of shallow landslide susceptibility by means of multivariate statistical techniques","volume":"26","author":"Baeza","year":"2010","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1007\/s10346-009-0183-2","article-title":"Regional landslide susceptibility analysis using back-propagation neural network model at Cameron Highland, Malaysia","volume":"7","author":"Pradhan","year":"2010","journal-title":"Landslides"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.catena.2019.104211","article-title":"GIS-based landslide susceptibility mapping for a part of the North Anatolian fault Zone between Re\u015fadiye and Koyulhisar (Turkey)","volume":"183","author":"Demir","year":"2019","journal-title":"Catena"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1007\/s10346-004-0039-8","article-title":"An approach for GIS-based statistical landslide susceptibility zonation\u2014with a case study in the Himalayas","volume":"2","author":"Saha","year":"2005","journal-title":"Landslides"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.enggeo.2005.02.002","article-title":"Landslide susceptibility mapping: A comparison of logistic regression and neural networks methods in a medium scale study, Hendek Region (Turkey)","volume":"79","author":"Yesilnacar","year":"2005","journal-title":"Eng. Geol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cageo.2015.04.007","article-title":"Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling","volume":"81","author":"Goetz","year":"2015","journal-title":"Comput. Geosci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.geomorph.2018.06.006","article-title":"Comparison of GIS-based landslide susceptibilitymodels using frequency ratio, logistic regression, and artificial neural network in a tertiary region of Ambon, Indonesia","volume":"318","author":"Aditian","year":"2018","journal-title":"Geomorphology"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.enggeo.2011.09.006","article-title":"Landslide susceptibility assessment using SVM machine learning algorithm","volume":"123","author":"Bajat","year":"2011","journal-title":"Eng. Geol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.catena.2016.09.007","article-title":"Hybrid integration of multilayer perceptron neural networks and machine learning ensembles for landslide susceptibility assessment at Himalayan Area (India) using GIS","volume":"149","author":"Pham","year":"2017","journal-title":"Catena"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2933","DOI":"10.3390\/rs12182933","article-title":"Application of machine learning to debris flow susceptibility mapping along the China-Pakistan Karakoram highway","volume":"12","author":"Feng","year":"2020","journal-title":"Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1897","DOI":"10.1007\/s10346-020-01392-9","article-title":"Machine learning ensemble modelling as a tool to improve landslide susceptibility mapping reliability","volume":"17","author":"Napoli","year":"2020","journal-title":"Landslides"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.geomorph.2020.107125","article-title":"AI-based identification of low-frequency debris flow catchments in the Bailong River Basin, China","volume":"359","author":"Zhao","year":"2020","journal-title":"Geomorphology"},{"key":"ref_38","first-page":"100","article-title":"Characteristics and causes of assembled geo-hazards induced by the rainstorm on 25th July 2013 in Tianshui City, Gansu, China","volume":"1","author":"Guo","year":"2015","journal-title":"Mt. Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/0013-7952(94)90001-9","article-title":"The loess of north-Central China: Geotechnical properties and their relation to slope stability","volume":"36","author":"Dijkstra","year":"1994","journal-title":"Eng. Geol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/0148-9062(94)90457-X","article-title":"A study on the generating mechanism of vertical joints in loess","volume":"31","author":"Wang","year":"1994","journal-title":"Int. J. Rock Mech. Min. Sci. Geomech."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.enggeo.2019.02.021","article-title":"Physical model experiments for shallow failure in rainfall-triggered loess slope, Northwest China","volume":"78","author":"Sun","year":"2019","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"663","DOI":"10.5194\/hess-10-663-2006","article-title":"A new method for determination of most likely landslide initiation points and the evaluation of digital terrain model scale in terrain stability mapping","volume":"10","author":"Tarolli","year":"2006","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2009WR008812","article-title":"Testing space-scale methodologies for automatic geomorphic feature extraction from lidar in a complex mountainous landscape","volume":"46","author":"Passalacqua","year":"2010","journal-title":"Water Resour. Res."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s11069-010-9695-2","article-title":"Geomorphic features extraction from high-resolution topography: Landslide crowns and bank erosion","volume":"61","author":"Tarolli","year":"2012","journal-title":"Nat. Hazards"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.geomorph.2019.05.001","article-title":"Inventory of rock glaciers in Himachal Himalaya, India using high-resolution Google Earth imagery","volume":"340","author":"Pandey","year":"2019","journal-title":"Geomorphology"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Clague, J.J., and Stead, D. (2012). Landslides: Types, Mechanisms and Modeling, Cambridge University Press.","DOI":"10.1017\/CBO9780511740367"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1007\/s10346-017-0871-2","article-title":"Landslides types controlled by tectonics-induced evolution of valley slopes (northern Apennines, Italy)","volume":"15","author":"Carlini","year":"2018","journal-title":"Landslides"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1007\/s11069-018-3219-x","article-title":"Tectonic and lithologic control over landslide activity within the Larji\u2013Kullu tectonic window in the higher Himalayas of India","volume":"92","author":"Mishra","year":"2018","journal-title":"Nat. Hazards"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s10346-013-0418-0","article-title":"A loess landslide induced by excavation and rainfall","volume":"11","author":"Wang","year":"2014","journal-title":"Landslides"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.enggeo.2014.08.015","article-title":"Heavy rainfall triggered loess\u2013mudstone landslide and subsequent debris flow in Tianshui, China","volume":"186","author":"Peng","year":"2015","journal-title":"Eng. Geol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.geomorph.2017.11.009","article-title":"Rainfall thresholds for the activation of shallow landslides in the Italian Alps: The role of environmental conditioning factors","volume":"303","author":"Palladino","year":"2018","journal-title":"Geomorphology"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1007\/s10346-013-0438-9","article-title":"Rainfall thresholds for prediction of shallow landslides around Chamoli-Joshimath region, Garhwal Himalayas, India","volume":"11","author":"Kanungo","year":"2014","journal-title":"Landslides"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2007JF000789","article-title":"Aspect-related microclimatic influences on slope forms and processes, northeastern Arizona","volume":"113","author":"Burnett","year":"2008","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.geomorph.2017.02.007","article-title":"Deep-seated landslides affecting monoclinal flysch morphostructure: Evaluation of LiDAR-derived topography of the highest range of the Czech Carpathians","volume":"285","year":"2017","journal-title":"Geomorphology"},{"key":"ref_55","unstructured":"Wilson, J.P., and Gallant, J.C. (2000). Terrain Analysis Principles and Applications, Wiley."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.geomorph.2020.107124","article-title":"Parameter-free delineation of slope units and terrain subdivision of Italy","volume":"358","author":"Alvioli","year":"2020","journal-title":"Geomorphology"},{"key":"ref_57","first-page":"79","article-title":"Some aspects of the geomorphic processes triggered by an extreme rainfall event: The November 1982 flood in the eastern Pyrenees","volume":"13","author":"Gallart","year":"1988","journal-title":"Catena Suppl."},{"key":"ref_58","unstructured":"Z\u00e1ruba, Q., and Mencl, V. (1969). Landslides and Their Control, Elsevier."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"131","DOI":"10.2208\/jscej1969.1983.338_131","article-title":"A prediction system for the site of probable surface failure of mountain-slope by topographical factors","volume":"338","author":"Okimura","year":"1983","journal-title":"Proc. Jpn. Soc. Civil Eng."},{"key":"ref_60","unstructured":"Oyagi, N. (1984, January 16\u201321). Landslides in Weathered Rocks and Residual Soils in Japan and Surrounding Areas: A State of the Art Report. Proceedings of the 4th International Symposium on Landslides, Toronto, ON, Canada."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11104-009-0159-y","article-title":"Desirable plant root traits for protecting natural and engineered slopes against landslides","volume":"324","author":"Stokes","year":"2009","journal-title":"Plant Soil"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.enggeo.2015.07.005","article-title":"Deep-seated gravitational deformation ofmountain slopes caused by river incision in the Central Range, Taiwan: Spatial distribution and geological characteristics","volume":"196","author":"Tsou","year":"2015","journal-title":"Eng. Geol."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","article-title":"Smote: Synthetic minorityover-sampling technique","volume":"16","author":"Chawla","year":"2002","journal-title":"J. Artif. Intell. Res."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Bisong, E. (2019). Introduction to Scikit-learn. Building Machine Learning and Deep Learning Models on Google Cloud Platform, Apress.","DOI":"10.1007\/978-1-4842-4470-8"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s10346-004-0042-0","article-title":"Distribution of landslides in southwest New Zealand","volume":"2","author":"Korup","year":"2005","journal-title":"Landslides"},{"key":"ref_66","first-page":"975","article-title":"Probability estimates for multi-class classification by pairwise coupling","volume":"5","author":"Wu","year":"2004","journal-title":"J. Mach. Learn. Res."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Roy, J., Saha, S., Arabameri, A., Blaschke, T., and Bui, D.T. (2019). A novel ensemble approach for landslide susceptibility mapping (ISM) in Darjeeling and Kalimpong districts, West Bengal, India. Remote Sens., 11.","DOI":"10.3390\/rs11232866"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1097\/00010694-196008000-00007","article-title":"An example of the role of microclimate in soil genesis","volume":"90","author":"Cooper","year":"1960","journal-title":"Soil Sci."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1080\/07929978.1999.10676751","article-title":"Biodiversity and interslope divergence of vascular plants caused by microclimate differences at \u201cEvolution Canyon\u201d lower nahal Oren, Mount Carmel, Israel","volume":"47","author":"Nevo","year":"1999","journal-title":"Isr. J. Plant Sci."},{"key":"ref_70","first-page":"27","article-title":"Researches on root distribution characteristics of Robinia Pseudoacacia stand in Wangdonggou on different site conditions","volume":"31","author":"Xue","year":"2003","journal-title":"J. Agric. Sci. Technol."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/S0016-7061(98)00014-7","article-title":"Changes in microstructure, voids and b-fabric of surface samples of a Vertisol caused by wet\/dry cycles","volume":"85","author":"Hussein","year":"1998","journal-title":"Geoderma"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1016\/j.nimb.2004.12.118","article-title":"Gammaray computed tomography to evaluate wetting\/drying soil structure changes","volume":"229","author":"Luiz","year":"2005","journal-title":"Nucl. Instrum. Methods Phys. Res."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.geomorph.2005.07.018","article-title":"Changes in land cover and shallow landslide activity: A case study in the Spanish Pyrenees","volume":"74","author":"Begueria","year":"2006","journal-title":"Geomorphology"},{"key":"ref_74","first-page":"935","article-title":"Gravity-driven groundwater flow and slope failure potential 2. Effects of slope morphology, material properties, and hydraulic heterogeneity","volume":"3","author":"Reid","year":"1992","journal-title":"Water Resour. Res."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1819\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:57:52Z","timestamp":1760162272000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1819"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,7]]},"references-count":74,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13091819"],"URL":"https:\/\/doi.org\/10.3390\/rs13091819","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,7]]}}}