{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T06:52:31Z","timestamp":1772952751574,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2022,7,27]],"date-time":"2022-07-27T00:00:00Z","timestamp":1658880000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41974148"],"award-info":[{"award-number":["41974148"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2020SK2135"],"award-info":[{"award-number":["2020SK2135"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021-15"],"award-info":[{"award-number":["2021-15"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["202012"],"award-info":[{"award-number":["202012"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100019091","name":"Key research and development program of Hunan Province of China","doi-asserted-by":"publisher","award":["41974148"],"award-info":[{"award-number":["41974148"]}],"id":[{"id":"10.13039\/501100019091","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100019091","name":"Key research and development program of Hunan Province of China","doi-asserted-by":"publisher","award":["2020SK2135"],"award-info":[{"award-number":["2020SK2135"]}],"id":[{"id":"10.13039\/501100019091","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100019091","name":"Key research and development program of Hunan Province of China","doi-asserted-by":"publisher","award":["2021-15"],"award-info":[{"award-number":["2021-15"]}],"id":[{"id":"10.13039\/501100019091","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100019091","name":"Key research and development program of Hunan Province of China","doi-asserted-by":"publisher","award":["202012"],"award-info":[{"award-number":["202012"]}],"id":[{"id":"10.13039\/501100019091","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Resources Research Project in Hunan Province of China","award":["41974148"],"award-info":[{"award-number":["41974148"]}]},{"name":"Natural Resources Research Project in Hunan Province of China","award":["2020SK2135"],"award-info":[{"award-number":["2020SK2135"]}]},{"name":"Natural Resources Research Project in Hunan Province of China","award":["2021-15"],"award-info":[{"award-number":["2021-15"]}]},{"name":"Natural Resources Research Project in Hunan Province of China","award":["202012"],"award-info":[{"award-number":["202012"]}]},{"name":"Department of Transportation of Hunan Province of China","award":["41974148"],"award-info":[{"award-number":["41974148"]}]},{"name":"Department of Transportation of Hunan Province of China","award":["2020SK2135"],"award-info":[{"award-number":["2020SK2135"]}]},{"name":"Department of Transportation of Hunan Province of China","award":["2021-15"],"award-info":[{"award-number":["2021-15"]}]},{"name":"Department of Transportation of Hunan Province of China","award":["202012"],"award-info":[{"award-number":["202012"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Although electrical resistivity tomography (ERT) may gather the internal resistivity information from a landslide area in a large-scale, low-cost, and non-invasive manner compared to point-based sensor monitoring technology, the indirect resistivity information obtained cannot directly evaluate the landslide\u2019s current mechanical status, such as stress, strength, etc. Based on ERT monitoring data, a framework for quantitatively and directly evaluating the evolution of the factor of safety (FOS) of landslides during rainfall is proposed. The framework first inverts ERT observation data using the inexact Gauss\u2013Newton method based on multiple constraints to obtain a more realistic resistivity distribution, then calculates the saturation distribution using Archie\u2019s equation, and finally calculates the FOS of landslides using the finite element strength reduction method. Twelve sets of numerical experiments were designed and carried out based on the synthetic data of a theoretical model. The experimental results show that the proposed framework is valid and reliable under various arrays, apparent resistivity noise, and uncertainty in the water-electric correlation curve, with the Dipole-Dipole array outperforming the others in terms of accuracy, sensitivity, and anti-noise capability. The proposed framework is significant in improving ERT monitoring and early warning capabilities for rainfall-induced landslides.<\/jats:p>","DOI":"10.3390\/rs14153592","type":"journal-article","created":{"date-parts":[[2022,7,28]],"date-time":"2022-07-28T03:21:16Z","timestamp":1658978476000},"page":"3592","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Using Electrical Resistivity Tomography to Monitor the Evolution of Landslides\u2019 Safety Factors under Rainfall: A Feasibility Study Based on Numerical Simulation"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8239-4469","authenticated-orcid":false,"given":"Dongxin","family":"Bai","sequence":"first","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"},{"name":"Hunan Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha 410083, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8014-819X","authenticated-orcid":false,"given":"Guangyin","family":"Lu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"},{"name":"Hunan Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha 410083, China"}]},{"given":"Ziqiang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"},{"name":"Hunan Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha 410083, China"}]},{"given":"Xudong","family":"Zhu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"},{"name":"Hunan Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha 410083, China"}]},{"given":"Chuanyi","family":"Tao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"},{"name":"Hunan Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha 410083, China"}]},{"given":"Ji","family":"Fang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of Education, School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"},{"name":"Hunan Key Laboratory of Non-Ferrous Resources and Geological Hazard Detection, Changsha 410083, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"928","DOI":"10.1080\/19475705.2020.1766580","article-title":"The design and application of landslide monitoring and early warning system based on microservice architecture","volume":"11","author":"Bai","year":"2020","journal-title":"Geomat. Nat. Hazards Risk"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Xia, C., Lu, G., Bai, D., Zhu, Z., Luo, S., and Zhang, G. (2020). Sensitivity Analyses of the Seepage and Stability of Layered Rock Slope Based on the Anisotropy of Hydraulic Conductivity: A Case Study in the Pulang Region of Southwestern China. Water, 12.","DOI":"10.3390\/w12082314"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Bai, D., Lu, G., Zhu, Z., Zhu, X., Tao, C., and Fang, J. (2022). A Hybrid Early Warning Method for the Landslide Acceleration Process Based on Automated Monitoring Data. Appl. Sci., 12.","DOI":"10.3390\/app12136478"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3783","DOI":"10.1007\/s10064-021-02136-2","article-title":"Prediction of landslide displacement with step-like curve using variational mode decomposition and periodic neural network","volume":"80","author":"Liu","year":"2021","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1153","DOI":"10.1007\/s10346-020-01563-8","article-title":"Modeling of rainfall-induced landslides using a full-scale flume test","volume":"18","author":"Lee","year":"2021","journal-title":"Landslides"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1033","DOI":"10.1016\/j.sandf.2021.05.010","article-title":"Rainfall-induced unstable slope monitoring and early warning through tilt sensors","volume":"61","author":"Sheikh","year":"2021","journal-title":"Soils Found."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"106383","DOI":"10.1016\/j.enggeo.2021.106383","article-title":"Prediction of seasonal variation of in-situ hydrologic behavior using an analytical transient infiltration model","volume":"294","author":"Ahmed","year":"2021","journal-title":"Eng. Geol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3149","DOI":"10.1007\/s10346-021-01699-1","article-title":"A three-dimensional large-deformation random finite-element study of landslide runout considering spatially varying soil","volume":"18","author":"Chen","year":"2021","journal-title":"Landslides"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3367","DOI":"10.1007\/s10346-021-01681-x","article-title":"Hydrological control of soil thickness spatial variability on the initiation of rainfall-induced shallow landslides using a three-dimensional model","volume":"18","author":"Tufano","year":"2021","journal-title":"Landslides"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"106348","DOI":"10.1016\/j.enggeo.2021.106348","article-title":"Coupled characterization of stratigraphic and geo-properties uncertainties\u2013A conditional random field approach","volume":"294","author":"Gong","year":"2021","journal-title":"Eng. Geol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"54","DOI":"10.2118\/942054-G","article-title":"The Electrical Resistivity Log as an Aid in Determining Some Reservoir Characteristics","volume":"146","author":"Archie","year":"1942","journal-title":"Trans. AIME"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"07005","DOI":"10.1051\/e3sconf\/20160907005","article-title":"Exploring ice content on partially saturated frozen soils using dielectric permittivity and bulk electrical conductivity measurements","volume":"9","author":"Mao","year":"2016","journal-title":"E3S Web Conf."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.jappgeo.2015.11.005","article-title":"Measurement and modelling of moisture\u2014electrical resistivity relationship of fine-grained unsaturated soils and electrical anisotropy","volume":"124","author":"Merritt","year":"2016","journal-title":"J. Appl. Geophys."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"e9491979","DOI":"10.1155\/2022\/9491979","article-title":"Estimation of Water Saturation in Shale Formation Using In Situ Multifrequency Dielectric Permittivity","volume":"2022","author":"Cho","year":"2022","journal-title":"Geofluids"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"104156","DOI":"10.1016\/j.advwatres.2022.104156","article-title":"Fine-scale heterogeneous structure impact on the scale-dependency of the effective hydro-electrical relations of unsaturated soils","volume":"162","author":"Moreno","year":"2022","journal-title":"Adv. Water Resour."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1007\/s12665-019-8430-x","article-title":"Electrical resistivity tomography (ERT) based subsurface characterisation of Pakhi Landslide, Garhwal Himalayas, India","volume":"78","author":"Falae","year":"2019","journal-title":"Environ. Earth Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.jappgeo.2006.01.001","article-title":"Investigation of a slope endangered by rainfall-induced landslides using 3D resistivity tomography and geotechnical testing","volume":"60","author":"Friedel","year":"2006","journal-title":"J. Appl. Geophys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"595","DOI":"10.5194\/hess-17-595-2013","article-title":"Three-dimensional monitoring of soil water content in a maize field using Electrical Resistivity Tomography","volume":"17","author":"Beff","year":"2013","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1029\/2018RG000603","article-title":"Geophysical Monitoring of Moisture-Induced Landslides: A Review","volume":"57","author":"Whiteley","year":"2019","journal-title":"Rev. Geophys."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Lapenna, V., and Perrone, A. (2022). Time-Lapse Electrical Resistivity Tomography (TL-ERT) for Landslide Monitoring: Recent Advances and Future Directions. Appl. Sci., 12.","DOI":"10.3390\/app12031425"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.earscirev.2014.04.002","article-title":"Electrical resistivity tomography technique for landslide investigation: A review","volume":"135","author":"Perrone","year":"2014","journal-title":"Earth-Sci. Rev."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1007\/s00254-006-0194-4","article-title":"Application of electrical resistivity tomography technique for investigation of landslides: A case from Turkey","volume":"50","author":"Drahor","year":"2006","journal-title":"Environ. Geol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Podolszki, L., Kosovi\u0107, I., Novosel, T., and Kure\u010di\u0107, T. (2022). Multi-Level Sensing Technologies in Landslide Research\u2014Hrvatska Kostajnica Case Study, Croatia. Sensors, 22.","DOI":"10.3390\/s22010177"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.jappgeo.2017.01.023","article-title":"Electric-field response based experimental investigation of unsaturated soil slope seepage","volume":"138","author":"Geng","year":"2017","journal-title":"J. Appl. Geophys."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"04019037","DOI":"10.1061\/(ASCE)HE.1943-5584.0001845","article-title":"Geoelectric Field Response to Seepage in Sand and Clay Formations","volume":"24","author":"Liu","year":"2019","journal-title":"J. Hydrol. Eng."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"103844","DOI":"10.1016\/j.jappgeo.2019.103844","article-title":"Geoelectrical characterization and monitoring of slopes on a rainfall-triggered landslide simulator","volume":"170","author":"Hojat","year":"2019","journal-title":"J. Appl. Geophys."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1111\/gwmr.12352","article-title":"Real-Time Geoelectric Monitoring of Seepage into Sand and Clay Layer","volume":"39","author":"Lyu","year":"2019","journal-title":"Ground Water Monit. Remediat."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1016\/j.jhydrol.2016.07.033","article-title":"Characterizing hydrological processes on loess slopes using electrical resistivity tomography\u2013A case study of the Heifangtai Terrace, Northwest China","volume":"541","author":"Zeng","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1002\/2016JF003983","article-title":"Four-Dimensional Imaging of Moisture Dynamics during Landslide Reactivation: Imaging of Landslide Moisture Dynamics","volume":"122","author":"Uhlemann","year":"2016","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.1093\/gji\/ggx453","article-title":"Jointly reconstructing ground motion and resistivity for ERT-based slope stability monitoring","volume":"212","author":"Boyle","year":"2017","journal-title":"Geophys. J. Int."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.enggeo.2019.04.009","article-title":"In-situ geophysical and hydro-geochemical monitoring to infer landslide dynamics (P\u00e9gairolles-de-l\u2019Escalette landslide, France)","volume":"254","author":"Denchik","year":"2019","journal-title":"Eng. Geol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2689","DOI":"10.1007\/s10346-021-01666-w","article-title":"A linked geomorphological and geophysical modelling methodology applied to an active landslide","volume":"18","author":"Boyd","year":"2021","journal-title":"Landslides"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.jcp.2014.11.035","article-title":"An iterative particle filter approach for coupled hydro-geophysical inversion of a controlled infiltration experiment","volume":"283","author":"Manoli","year":"2015","journal-title":"J. Comput. Phys."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.jappgeo.2017.08.002","article-title":"Forward modeling to investigate inversion artifacts resulting from time-lapse electrical resistivity tomography during rainfall simulations","volume":"145","author":"Carey","year":"2017","journal-title":"J. Appl. Geophys."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.enggeo.2017.11.012","article-title":"Assessment of active landslides using field electrical measurements","volume":"233","author":"Crawford","year":"2018","journal-title":"Eng. Geol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.jappgeo.2018.06.009","article-title":"Using 2-D electrical resistivity imaging for joint geophysical and geotechnical characterization of shallow landslides","volume":"157","author":"Crawford","year":"2018","journal-title":"J. Appl. Geophys."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.enggeo.2019.02.015","article-title":"Long-term landslide monitoring using soil-water relationships and electrical data to estimate suction stress","volume":"251","author":"Crawford","year":"2019","journal-title":"Eng. Geol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"H1","DOI":"10.1190\/1.2402499","article-title":"RESINVM3D: A 3D resistivity inversion package","volume":"72","author":"Pidlisecky","year":"2007","journal-title":"Geophysics"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1007\/s11771-012-1021-6","article-title":"Multiple linear system techniques for 3D finite element method modeling of direct current resistivity","volume":"19","author":"Li","year":"2012","journal-title":"J. Cent. South Univ."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Liu, W., Wang, H., Xi, Z., Zhang, R., and Huang, X. (2022). Physics-Driven Deep Learning Inversion with Application to Magnetotelluric. Remote Sens., 14.","DOI":"10.3390\/rs14133218"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1319","DOI":"10.1093\/gji\/ggab024","article-title":"Convolutional neural networks with SegNet architecture applied to three-dimensional tomography of subsurface electrical resistivity: CNN-3D-ERT","volume":"225","author":"Vu","year":"2021","journal-title":"Geophys. J. Int."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Tikhonov, A.N., Goncharsky, A., Stepanov, V.V., and Yagola, A.G. (1995). Numerical Methods for the Solution of Ill-Posed Problems, Springer Science & Business Media.","DOI":"10.1007\/978-94-015-8480-7"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/s002110050078","article-title":"Using the L--curve for determining optimal regularization parameters","volume":"69","author":"Engl","year":"1994","journal-title":"Numer. Math."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"892","DOI":"10.2136\/sssaj1980.03615995004400050002x","article-title":"A Closed-form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils","volume":"44","year":"1980","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_45","unstructured":"Lv, Y. (2020). Study on Stability of Unsaturated Soil Slope under Rainfall Condition Based on Xingye District. [Master\u2019s Thesis, Guilin University of Technology]."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1007\/s11430-013-4586-5","article-title":"Application of synoptic-scale anomalous winds predicted by medium-range weather forecast models on the regional heavy rainfall in China in 2010","volume":"56","author":"Qian","year":"2013","journal-title":"Sci. China Earth Sci."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1007\/s12665-022-10410-z","article-title":"Integrated analysis of geophysical approaches for slope failure characterisation","volume":"81","author":"Zakaria","year":"2022","journal-title":"Environ. Earth Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/15\/3592\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:57:24Z","timestamp":1760140644000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/15\/3592"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,27]]},"references-count":47,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2022,8]]}},"alternative-id":["rs14153592"],"URL":"https:\/\/doi.org\/10.3390\/rs14153592","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,27]]}}}