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Landslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andes

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dc.contributor.advisorAristizábal, Edier
dc.contributor.authorRuiz Vásquez, Diana
dc.coverage.spatialMedellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees
dc.creator.emaildiruva123@gmail.comspa
dc.date.accessioned2019-03-11T19:39:00Z
dc.date.available2019-03-11T19:39:00Z
dc.date.issued2017
dc.description.abstractLandslides triggered by rainfall are one of the most frequent causes for natural disasters in the tropical and mountainous countries, such as Colombia. However landslide susceptibility assessments are often limited due to the scarcity of reliable observations and available information, particularly in remote high-mountain regions. Although Colombia is a tropical and mountainous terrains dominated by landslide prone region, it has little availability of data for landslide susceptibility assessment. This study presents the application of a logistic regression model to assess landslide susceptibility in the La Liboariana catchment. It is a basin on a tropical inaccessible terrain in northern Colombian Andes, where on May 18th, 2015, more than 40 landslides and an associated flash flood and debris flow afterwards killed 104 inhabitants. The applied approach is based on free access remote sensing tools to complete and obtain the missing landslide causative factors. To select key factors related to landslide occurrence the prediction and successes performance of the susceptibility maps for each combination of landslide causative factors was estimated using the Receiver Operating Characteristics (ROC). The results show that only three factors gave the best predicting accuracy. All the factors were obtained by free remote sensing tools, indicating they can provide enough information to achieve a successful approach to landslide susceptibility assessment in complex terrains as the study area. This suggests that the proposed approach could be implemented in several tropical regions with similar characteristics based only in free access information.spa
dc.description.degreelevelTrabajospa
dc.description.degreenameGeólogo(a)spa
dc.format.mimetypeapplication/pdf
dc.identifier.ddc551.307CD R934L
dc.identifier.instnameinstname:Universidad EAFIT
dc.identifier.reponamereponame:Repositorio Institucional Universidad EAFIT
dc.identifier.repourlrepourl:https://repository.eafit.edu.co
dc.identifier.urihttps://hdl.handle.net/10784/13473
dc.language.isospa
dc.publisherUniversidad EAFITspa
dc.publisher.departmentDepartamento de Geologíaspa
dc.publisher.facultyEscuela de Cienciasspa
dc.publisher.placeMedellínspa
dc.publisher.programGeologíaspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2
dc.rights.localAcceso abierto
dc.subjectDesprendimientos de tierraspa
dc.subject.keywordGISspa
dc.subject.keywordLogistic regressionspa
dc.subject.keywordRemote sensingspa
dc.subject.keywordLandslide susceptibilityspa
dc.subject.keywordTropical basinspa
dc.subject.keywordColombiaspa
dc.subject.lembDESPRENDIMIENTOS DE TIERRA - SALGAR (ANTIOQUIA, COLOMBIA)spa
dc.subject.lembSENSORES REMOTOSspa
dc.subject.lembSISTEMAS DE INFORMACIÓN GEOGRÁFICAspa
dc.titleLandslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andes
dc.typeinfo:eu-repo/semantics/bachelorThesis
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1f
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.localTrabajo de gradospa
dc.type.redcolhttp://purl.org/redcol/resource_type/TP
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dspace.entity.typePublication

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