{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T19:16:21Z","timestamp":1776107781893,"version":"3.50.1"},"reference-count":178,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T00:00:00Z","timestamp":1663027200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Landslides (LS) represent geomorphological processes that can induce changes over time in the physical, hydrogeological, and mechanical properties of the involved materials. For geohazard assessment, the variations of these properties might be detected by a wide range of non-intrusive techniques, which can sometimes be confusing due to their significant variation in accuracy, suitability, coverage area, logistics, timescale, cost, and integration potential; this paper reviews common geophysical methods (GM) categorized as Emitted Seismic and Ambient Noise based and proposes an integrated approach between them for improving landslide studies; this level of integration (among themselves) is an important step ahead of integrating geophysical data with remote sensing data. The aforementioned GMs help to construct a framework based on physical properties that may be linked with site characterization (e.g., a landslide and its subsurface channel geometry, recharge pathways, rock fragments, mass flow rate, etc.) and dynamics (e.g., quantification of the rheology, saturation, fracture process, toe erosion, mass flow rate, deformation marks and spatiotemporally dependent geogenic pore-water pressure feedback through a joint analysis of geophysical time series, displacement and hydrometeorological measurements from the ground, air and space). A review of the use of unmanned aerial vehicles (UAV) based photogrammetry for the investigation of landslides was also conducted to highlight the latest advancement and discuss the synergy between UAV and geophysical in four possible broader areas: (i) survey planning, (ii) LS investigation, (iii) LS dynamics and (iv) presentation of results in GIS environment. Additionally, endogenous source mechanisms lead to the appearance of deformation marks on the surface and provide ground for the integrated use of UAV and geophysical monitoring for landslide early warning systems. Further development in this area requires UAVs to adopt more multispectral and other advanced sensors where their data are integrated with the geophysical one as well as the climatic data to enable Artificial Intelligent based prediction of LS.<\/jats:p>","DOI":"10.3390\/rs14184564","type":"journal-article","created":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T22:37:28Z","timestamp":1663108648000},"page":"4564","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":70,"title":["Review on the Geophysical and UAV-Based Methods Applied to Landslides"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4155-6764","authenticated-orcid":false,"given":"Yawar","family":"Hussain","sequence":"first","affiliation":[{"name":"Georisk and Environment, Department of Geology, University of Liege, 4000 Liege, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2482-2522","authenticated-orcid":false,"given":"Romy","family":"Schl\u00f6gel","sequence":"additional","affiliation":[{"name":"Georisk and Environment, Department of Geology, University of Liege, 4000 Liege, Belgium"},{"name":"Signal Processing Laboratory, Centre Spatial of Li\u00e8ge, 4031 Li\u00e8ge, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9789-6736","authenticated-orcid":false,"given":"Agnese","family":"Innocenti","sequence":"additional","affiliation":[{"name":"Department of Earth Sciences, University of Florence, 50121 Firenze, Italy"},{"name":"Department of Agriculture, Food, Environment and Forestry, University of Florence, 50144 Firenze, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5048-0423","authenticated-orcid":false,"given":"Omar","family":"Hamza","sequence":"additional","affiliation":[{"name":"College of Science and Engineering, University of Derby, Derby DE22 3AW, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1231-8158","authenticated-orcid":false,"given":"Roberto","family":"Iannucci","sequence":"additional","affiliation":[{"name":"Dipartimento di Scienze Della Terra and Centro di Ricerca per i Rischi Geologici CERI, Sapienza Universit\u00e0 di Roma, P.le A. Moro 5, 00185 Roma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1277-7784","authenticated-orcid":false,"given":"Salvatore","family":"Martino","sequence":"additional","affiliation":[{"name":"Dipartimento di Scienze Della Terra and Centro di Ricerca per i Rischi Geologici CERI, Sapienza Universit\u00e0 di Roma, P.le A. Moro 5, 00185 Roma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3799-1242","authenticated-orcid":false,"given":"Hans-Balder","family":"Havenith","sequence":"additional","affiliation":[{"name":"Georisk and Environment, Department of Geology, University of Liege, 4000 Liege, Belgium"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,13]]},"reference":[{"key":"ref_1","unstructured":"Hearn, G., Petley, D., Hart, A., Massey, C., and Chant, C. (2003). 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