Landslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andes
Landslides 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...
- Autores:
-
Ruiz Vásquez, Diana
- Tipo de recurso:
- Fecha de publicación:
- 2017
- Institución:
- Universidad EAFIT
- Repositorio:
- Repositorio EAFIT
- Idioma:
- spa
- OAI Identifier:
- oai:repository.eafit.edu.co:10784/13473
- Acceso en línea:
- http://hdl.handle.net/10784/13473
- Palabra clave:
- Desprendimientos de tierra
DESPRENDIMIENTOS DE TIERRA - SALGAR (ANTIOQUIA, COLOMBIA)
SENSORES REMOTOS
SISTEMAS DE INFORMACIÓN GEOGRÁFICA
GIS
Logistic regression
Remote sensing
Landslide susceptibility
Tropical basin
Colombia
- Rights
- License
- Acceso abierto
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Aristizábal, EdierRuiz Vásquez, DianaGeólogodiruva123@gmail.comMedellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees2019-03-11T19:39:00Z20172019-03-11T19:39:00Zhttp://hdl.handle.net/10784/13473551.307CD R934LLandslides 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.spaUniversidad EAFITGeologíaEscuela de Ciencias. Departamento de GeologíaMedellínDesprendimientos de tierraDESPRENDIMIENTOS DE TIERRA - SALGAR (ANTIOQUIA, COLOMBIA)SENSORES REMOTOSSISTEMAS DE INFORMACIÓN GEOGRÁFICAGISLogistic regressionRemote sensingLandslide susceptibilityTropical basinColombiaLandslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andesinfo:eu-repo/semantics/bachelorThesisbachelorThesisTrabajo de gradoacceptedVersionhttp://purl.org/coar/resource_type/c_7a1fAcceso abiertohttp://purl.org/coar/access_right/c_abf2LICENSElicense.txtlicense.txttext/plain; charset=utf-82556https://repository.eafit.edu.co/bitstreams/3ed23f89-2641-447e-ba64-2ea66698dac9/download76025f86b095439b7ac65b367055d40cMD51ORIGINALDiana_RuizVásquez_2017.pdfDiana_RuizVásquez_2017.pdfTrabajo de gradoapplication/pdf9274209https://repository.eafit.edu.co/bitstreams/ada68799-6b36-4ea0-9514-04d6c8ff1c7c/downloadacbf8ae75e316e26256d55a9ba53c4dfMD5210784/13473oai:repository.eafit.edu.co:10784/134732019-03-11 14:39:00.632open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.co |
dc.title.spa.fl_str_mv |
Landslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andes |
title |
Landslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andes |
spellingShingle |
Landslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andes Desprendimientos de tierra DESPRENDIMIENTOS DE TIERRA - SALGAR (ANTIOQUIA, COLOMBIA) SENSORES REMOTOS SISTEMAS DE INFORMACIÓN GEOGRÁFICA GIS Logistic regression Remote sensing Landslide susceptibility Tropical basin Colombia |
title_short |
Landslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andes |
title_full |
Landslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andes |
title_fullStr |
Landslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andes |
title_full_unstemmed |
Landslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andes |
title_sort |
Landslide susceptibility assessment in mountainous and tropical scarce-data regions using remote sensing data : a case study in the Colombian Andes |
dc.creator.fl_str_mv |
Ruiz Vásquez, Diana |
dc.contributor.advisor.spa.fl_str_mv |
Aristizábal, Edier |
dc.contributor.author.none.fl_str_mv |
Ruiz Vásquez, Diana |
dc.subject.spa.fl_str_mv |
Desprendimientos de tierra |
topic |
Desprendimientos de tierra DESPRENDIMIENTOS DE TIERRA - SALGAR (ANTIOQUIA, COLOMBIA) SENSORES REMOTOS SISTEMAS DE INFORMACIÓN GEOGRÁFICA GIS Logistic regression Remote sensing Landslide susceptibility Tropical basin Colombia |
dc.subject.lemb.spa.fl_str_mv |
DESPRENDIMIENTOS DE TIERRA - SALGAR (ANTIOQUIA, COLOMBIA) SENSORES REMOTOS SISTEMAS DE INFORMACIÓN GEOGRÁFICA |
dc.subject.keyword.spa.fl_str_mv |
GIS Logistic regression Remote sensing Landslide susceptibility Tropical basin Colombia |
description |
Landslides 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. |
publishDate |
2017 |
dc.date.issued.none.fl_str_mv |
2017 |
dc.date.available.none.fl_str_mv |
2019-03-11T19:39:00Z |
dc.date.accessioned.none.fl_str_mv |
2019-03-11T19:39:00Z |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/bachelorThesis |
dc.type.eng.fl_str_mv |
bachelorThesis |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_7a1f |
dc.type.local.spa.fl_str_mv |
Trabajo de grado |
dc.type.hasVersion.eng.fl_str_mv |
acceptedVersion |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/10784/13473 |
dc.identifier.ddc.none.fl_str_mv |
551.307CD R934L |
url |
http://hdl.handle.net/10784/13473 |
identifier_str_mv |
551.307CD R934L |
dc.language.iso.spa.fl_str_mv |
spa |
language |
spa |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.local.spa.fl_str_mv |
Acceso abierto |
rights_invalid_str_mv |
Acceso abierto http://purl.org/coar/access_right/c_abf2 |
dc.coverage.spatial.none.fl_str_mv |
Medellín 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.publisher.spa.fl_str_mv |
Universidad EAFIT |
dc.publisher.program.spa.fl_str_mv |
Geología |
dc.publisher.department.spa.fl_str_mv |
Escuela de Ciencias. Departamento de Geología |
dc.publisher.place.spa.fl_str_mv |
Medellín |
institution |
Universidad EAFIT |
bitstream.url.fl_str_mv |
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repository.name.fl_str_mv |
Repositorio Institucional Universidad EAFIT |
repository.mail.fl_str_mv |
repositorio@eafit.edu.co |
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1814110101211971584 |