Learnings from rapid response efforts to remotely detect landslides triggered by the August 2021 Nippes earthquake and Tropical Storm Grace in Haiti

dc.contributor.authorAmatya, Pukar
dc.contributor.authorScheip, Corey
dc.contributor.authorDéprez, Aline
dc.contributor.authorMalet, Jean-Philippe
dc.contributor.authorSlaughter, Stephen L.
dc.contributor.authorHandwerger, Alexander L.
dc.contributor.authorEmberson, Robert
dc.contributor.authorKirschbaum, Dalia
dc.contributor.authorJean-Baptiste, Julien
dc.contributor.authorHuang, Mong-Han
dc.contributor.authorClark, Marin K.
dc.contributor.authorZekkos, Dimitrios
dc.contributor.authorHuang, Jhih-Rou
dc.contributor.authorPacini, Fabrizio
dc.contributor.authorBoissier, Enguerran
dc.date.accessioned2023-08-08T22:49:44Z
dc.date.available2023-08-08T22:49:44Z
dc.date.issued2023-07-22
dc.description.abstractOn August 14, 2021, a Mw 7.2 earthquake struck the Tiburon Peninsula of western Haiti triggering thousands of landslides. Three days after the earthquake on August 17, 2021, Tropical Storm Grace crossed shallow waters offshore of southern Haiti triggering more landslides worsening the situation. In the aftermath of these events, several organizations with disaster response capabilities or programs activated to provide information on the location of landslides to first responders on the ground. Utilizing remote sensing to support rapid response, one organization manually mapped initiation point of landslides and three automatically detected landslides. The 2021 Haiti event also provided a unique opportunity to test different automated landslide detection methods that utilized both SAR and optical data in a rapid response scenario where rapid situational awareness was critical. As the methods used are highly replicable, the main goal of this study is to summarize the landslide rapid response products released by the organizations, detection methods, quantify accuracy and provide guidelines on how some of the shortcomings encountered in this effort might be addressed in the future. To support this validation, a manually mapped polygon-based landslide inventory covering the entire affected area was created and is also released through this effort.en_US
dc.description.sponsorshipThis work was funded by the NASA’s Disaster Risk Reduction and Response 18-DISASTER18-0022, BGC Engineering, the ESA "Science Support Activity - SAT" initiative, the French Space Agency (CNES) and the Solid Earth datahub ForM@Ter of the French Research Infrastructure (RI) Data-Terra.en_US
dc.description.urihttps://link.springer.com/article/10.1007/s11069-023-06096-6en_US
dc.format.extent39 pagesen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/m2su84-dqoz
dc.identifier.citationAmatya, P., Scheip, C., Déprez, A. et al. Learnings from rapid response efforts to remotely detect landslides triggered by the August 2021 Nippes earthquake and Tropical Storm Grace in Haiti. Nat Hazards (2023). https://doi.org/10.1007/s11069-023-06096-6en_US
dc.identifier.urihttps://doi.org/10.1007/s11069-023-06096-6
dc.identifier.urihttp://hdl.handle.net/11603/29133
dc.language.isoen_USen_US
dc.publisherSpringeren_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC GESTAR II Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.en_US
dc.rightsPublic Domain Mark 1.0*
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.titleLearnings from rapid response efforts to remotely detect landslides triggered by the August 2021 Nippes earthquake and Tropical Storm Grace in Haitien_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0001-8008-4475en_US
dcterms.creatorhttps://orcid.org/0000-0002-2823-4453en_US

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