Assessment of susceptibility to landslides in the eastern cordillera of Colombia using the weight of evidence statistical method
Analyses of susceptible areas to landslides in mountain regions are a fundamental approach to identify areas prone to suffer future landslides, in order to prevent any natural disaster and associated life and infrastructure losses. In this project a statistical approach based on the Bayesian theorem...
- Autores:
-
Calderón Guevara, Wilmar Andrés
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2020
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/48951
- Acceso en línea:
- http://hdl.handle.net/1992/48951
- Palabra clave:
- Desprendimientos de tierra
Prevención de desastres
Evaluación de riesgos
Desastres naturales
Sistemas de información geográfica
Geociencias
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-sa/4.0/
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|
dc.title.es_CO.fl_str_mv |
Assessment of susceptibility to landslides in the eastern cordillera of Colombia using the weight of evidence statistical method |
title |
Assessment of susceptibility to landslides in the eastern cordillera of Colombia using the weight of evidence statistical method |
spellingShingle |
Assessment of susceptibility to landslides in the eastern cordillera of Colombia using the weight of evidence statistical method Desprendimientos de tierra Prevención de desastres Evaluación de riesgos Desastres naturales Sistemas de información geográfica Geociencias |
title_short |
Assessment of susceptibility to landslides in the eastern cordillera of Colombia using the weight of evidence statistical method |
title_full |
Assessment of susceptibility to landslides in the eastern cordillera of Colombia using the weight of evidence statistical method |
title_fullStr |
Assessment of susceptibility to landslides in the eastern cordillera of Colombia using the weight of evidence statistical method |
title_full_unstemmed |
Assessment of susceptibility to landslides in the eastern cordillera of Colombia using the weight of evidence statistical method |
title_sort |
Assessment of susceptibility to landslides in the eastern cordillera of Colombia using the weight of evidence statistical method |
dc.creator.fl_str_mv |
Calderón Guevara, Wilmar Andrés |
dc.contributor.advisor.none.fl_str_mv |
Nitescu, Bogdan Sánchez Silva, Edgar Mauricio |
dc.contributor.author.none.fl_str_mv |
Calderón Guevara, Wilmar Andrés |
dc.contributor.jury.none.fl_str_mv |
Pardo Villaveces, Natalia |
dc.subject.armarc.es_CO.fl_str_mv |
Desprendimientos de tierra Prevención de desastres Evaluación de riesgos Desastres naturales Sistemas de información geográfica |
topic |
Desprendimientos de tierra Prevención de desastres Evaluación de riesgos Desastres naturales Sistemas de información geográfica Geociencias |
dc.subject.themes.none.fl_str_mv |
Geociencias |
description |
Analyses of susceptible areas to landslides in mountain regions are a fundamental approach to identify areas prone to suffer future landslides, in order to prevent any natural disaster and associated life and infrastructure losses. In this project a statistical approach based on the Bayesian theorem was used to assess the susceptibility to landslides in an area on the eastern margin of the Eastern Cordillera of Colombia. Bayes theorem was employed by using the Weight Of Evidence (WOE) method to produce a susceptibility map of the study area. The fundamental assumption of the method is that future landslides will occur under circumstances similar to previous landslides. Modelling of landslide susceptibility was carried out by using geographical information systems (GIS) analysis and data integration. A series of 14 causative factors were analyzed to determine their relative contribution to landslide occurrence. The final susceptibility map is based on independent causative factors obtained through a X² non-parametric test. The algorithm used in this project accomplished model accuracies of 80.88% for the study area and 91.87% for a smaller area inside the original study area, which demonstrate its applicability |
publishDate |
2020 |
dc.date.issued.none.fl_str_mv |
2020 |
dc.date.accessioned.none.fl_str_mv |
2021-02-18T12:37:10Z |
dc.date.available.none.fl_str_mv |
2021-02-18T12:37:10Z |
dc.type.spa.fl_str_mv |
Trabajo de grado - Pregrado |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/bachelorThesis |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_7a1f |
dc.type.content.spa.fl_str_mv |
Text |
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http://purl.org/redcol/resource_type/TP |
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http://purl.org/coar/resource_type/c_7a1f |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/1992/48951 |
dc.identifier.pdf.none.fl_str_mv |
u833613.pdf |
dc.identifier.instname.spa.fl_str_mv |
instname:Universidad de los Andes |
dc.identifier.reponame.spa.fl_str_mv |
reponame:Repositorio Institucional Séneca |
dc.identifier.repourl.spa.fl_str_mv |
repourl:https://repositorio.uniandes.edu.co/ |
url |
http://hdl.handle.net/1992/48951 |
identifier_str_mv |
u833613.pdf instname:Universidad de los Andes reponame:Repositorio Institucional Séneca repourl:https://repositorio.uniandes.edu.co/ |
dc.language.iso.es_CO.fl_str_mv |
eng |
language |
eng |
dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.coar.spa.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.extent.es_CO.fl_str_mv |
46 hojas |
dc.format.mimetype.es_CO.fl_str_mv |
application/pdf |
dc.publisher.es_CO.fl_str_mv |
Universidad de los Andes |
dc.publisher.program.es_CO.fl_str_mv |
Geociencias |
dc.publisher.faculty.es_CO.fl_str_mv |
Facultad de Ciencias |
dc.publisher.department.es_CO.fl_str_mv |
Departamento de Geociencias |
dc.source.es_CO.fl_str_mv |
instname:Universidad de los Andes reponame:Repositorio Institucional Séneca |
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Universidad de los Andes |
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Universidad de los Andes |
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Repositorio Institucional Séneca |
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Repositorio Institucional Séneca |
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Al consultar y hacer uso de este recurso, está aceptando las condiciones de uso establecidas por los autores.http://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Nitescu, Bogdan98c78473-43b4-4659-ab3e-25e0970851a5400Sánchez Silva, Edgar Mauriciovirtual::6616-1Calderón Guevara, Wilmar Andrés57361700-258c-40dc-84c7-74d6939d3efe400Pardo Villaveces, Natalia2021-02-18T12:37:10Z2021-02-18T12:37:10Z2020http://hdl.handle.net/1992/48951u833613.pdfinstname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/Analyses of susceptible areas to landslides in mountain regions are a fundamental approach to identify areas prone to suffer future landslides, in order to prevent any natural disaster and associated life and infrastructure losses. In this project a statistical approach based on the Bayesian theorem was used to assess the susceptibility to landslides in an area on the eastern margin of the Eastern Cordillera of Colombia. Bayes theorem was employed by using the Weight Of Evidence (WOE) method to produce a susceptibility map of the study area. The fundamental assumption of the method is that future landslides will occur under circumstances similar to previous landslides. Modelling of landslide susceptibility was carried out by using geographical information systems (GIS) analysis and data integration. A series of 14 causative factors were analyzed to determine their relative contribution to landslide occurrence. The final susceptibility map is based on independent causative factors obtained through a X² non-parametric test. The algorithm used in this project accomplished model accuracies of 80.88% for the study area and 91.87% for a smaller area inside the original study area, which demonstrate its applicability"El análisis de áreas susceptibles a deslizamientos en zonas montañosas es una aproximación fundamental para identificar áreas en las que pueden ocurrir futuros deslizamientos, para así prevenir cualquier desastre natural y sus pérdidas de vidas e infraestructura asociadas. En este proyecto, un enfoque estadístico basado en el teorema de Bayes fue usado para evaluar la susceptibilidad a deslizamientos en un área en el flanco oriental de la Cordillera Oriental de Colombia. El teorema de bayes fue empleado utilizando el método Weight of Evidence (WOE) para producir un mapa de susceptibilidad en la zona de estudio. La asunción fundamental de este método es que futuros deslizamientos ocurrirán bajo circunstancias similares a los que causaron previos deslizamientos. La modelación de la susceptibilidad a deslizamientos fue llevada a cabo haciendo un análisis e integración de datos en un sistema de información geográfico (SIG). Una serie de 14 factores causativos fue analizada para determinar su contribución relativa a la ocurrencia de deslizamientos. El mapa final de susceptibilidad está basado en los factores causativos independientes obtenidos usando el test no paramétrico X². EL algoritmo utilizado en este proyecto logró una exactitud de 80.88% en el area de estudio y de 91.87% para un área de estudio más pequeña dentro del área de estudio original, demostrando así la aplicabilidad del método."--Tomado del Formato de Documento de GradoGeocientíficoPregrado46 hojasapplication/pdfengUniversidad de los AndesGeocienciasFacultad de CienciasDepartamento de Geocienciasinstname:Universidad de los Andesreponame:Repositorio Institucional SénecaAssessment of susceptibility to landslides in the eastern cordillera of Colombia using the weight of evidence statistical methodTrabajo de grado - Pregradoinfo:eu-repo/semantics/bachelorThesishttp://purl.org/coar/resource_type/c_7a1fhttp://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/TPDesprendimientos de tierraPrevención de desastresEvaluación de riesgosDesastres naturalesSistemas de información geográficaGeocienciasPublicationhttps://scholar.google.es/citations?user=0qgd0wkAAAAJvirtual::6616-10000-0002-3626-6690virtual::6616-1https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000076813virtual::6616-124c11e3d-0ed1-4dc6-8d0f-47041642d01fvirtual::6616-124c11e3d-0ed1-4dc6-8d0f-47041642d01fvirtual::6616-1TEXTu833613.pdf.txtu833613.pdf.txtExtracted texttext/plain77424https://repositorio.uniandes.edu.co/bitstreams/2e81b897-ee5b-45f4-a972-f4084f39e114/downloadd3f5912f7387fdf6555b1d2c56c703ccMD54ORIGINALu833613.pdfapplication/pdf5614579https://repositorio.uniandes.edu.co/bitstreams/d5c03aae-8f09-43e7-9056-fdd190a4bb1a/download80235553ade488bb7dc9f01d133fb044MD51THUMBNAILu833613.pdf.jpgu833613.pdf.jpgIM Thumbnailimage/jpeg9525https://repositorio.uniandes.edu.co/bitstreams/83005746-726b-4a4e-9160-cd92e66ded2c/downloaddc1ee963cb5fcd1cc86537881fca9562MD551992/48951oai:repositorio.uniandes.edu.co:1992/489512024-03-13 13:13:50.573http://creativecommons.org/licenses/by-nc-sa/4.0/open.accesshttps://repositorio.uniandes.edu.coRepositorio institucional Sénecaadminrepositorio@uniandes.edu.co |