Sentinel-1 SAR amplitude imagery for rapid landslide detection
Despite landslides impact the society worldwide every day, landslide information isinhomogeneous and lacking. When landslides occur in remote areas or where the availability ofoptical images is rare due to cloud persistence, they might remain unknown, or unnoticed for longtime, preventing studies an...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) |
| Repositorio: | r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) |
| OAI Identifier: | oai:cttc.fundanetsuite.com:p1229 |
| Acceso en línea: | https://cttc.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=1229 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064014108&doi=10.3390%2frs11070760&partnerID=40&md5=92e95fa29e376ea72bb2c4f5da30d7fe |
| Access Level: | acceso abierto |
| Palabra clave: | Landslides Mapping Accurate mapping Change detection Landslide detection SAR amplitude Spatial and temporal scale Strong earthquakes Systematic assessment Triggering factors Radar imaging |
| Sumario: | Despite landslides impact the society worldwide every day, landslide information isinhomogeneous and lacking. When landslides occur in remote areas or where the availability ofoptical images is rare due to cloud persistence, they might remain unknown, or unnoticed for longtime, preventing studies and hampering civil protection operations. The unprecedented availabilityof SAR C-band images provided by the Sentinel-1 constellation offers the opportunity to proposenew solutions to detect landslides events. In this work, we perform a systematic assessment ofSentinel-1 SAR C-band images acquired before and after known events. We present the resultsof a pilot study on 32 worldwide cases of rapid landslides entailing different types, sizes, slopeexpositions, as well as pre-existing land cover, triggering factors and climatic regimes. Results showthat in about eighty-four percent of the cases, changes caused by landslides on SAR amplitudesare unambiguous, whereas only in about thirteen percent of the cases there is no evidence. On theother hand, the signal does not allow for a systematic use to produce inventories because only in8 cases, a delineation of the landslide borders (i.e., mapping) can be manually attempted. In a fewcases, cascade multi-hazard (e.g., floods caused by landslides) and evidences of extreme triggeringfactors (e.g., strong earthquakes or very rapid snow melting) were detected. The method promises toincrease the availability of information on landslides at different spatial and temporal scales withbenefits for event magnitude assessment during weather-related emergencies, model tuning, andlandslide forecast model validation, in particular when accurate mapping is not required. © 2019 by the authors. |
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