Assessing population exposure for landslide risk analysis using dasymetric cartography
Autor(a) principal: | |
---|---|
Data de Publicação: | 2016 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10451/28116 |
Resumo: | Assessing the number and locations of exposed people is a crucial step in landslide risk management and emergency planning. The available population statistical data frequently have insufficient detail for an accurate assessment of potentially exposed people to hazardous events, mainly when they occur at the local scale, such as with landslides. The present study aims to apply dasymetric cartography to improving population spatial resolution and to assess the potentially exposed population. An additional objective is to compare the results with those obtained with a more common approach that uses, as spatial units, basic census units, which are the best spatial data disaggregation and detailed information available for regional studies in Portugal. Considering the Portuguese census data and a layer of residential building footprint, which was used as ancillary information, the number of exposed inhabitants differs significantly according to the approach used. When the census unit approach is used, considering the three highest landslide susceptible classes, the number of exposed inhabitants is in general overestimated. Despite the associated uncertainties of a general cost–benefit analysis, the presented methodology seems to be a reliable approach for gaining a first approximation of a more detailed estimation of exposed people. The approach based on dasymetric cartography allows the spatial resolution of population over large areas to be increased and enables the use of detailed landslide susceptibility maps, which are valuable for improving the exposed population assessment. |
id |
RCAP_06f9492b050e26b545b6a5918c50981e |
---|---|
oai_identifier_str |
oai:repositorio.ul.pt:10451/28116 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Assessing population exposure for landslide risk analysis using dasymetric cartographypopulation exposurelandsliderisk analysisdasymetric cartographyAssessing the number and locations of exposed people is a crucial step in landslide risk management and emergency planning. The available population statistical data frequently have insufficient detail for an accurate assessment of potentially exposed people to hazardous events, mainly when they occur at the local scale, such as with landslides. The present study aims to apply dasymetric cartography to improving population spatial resolution and to assess the potentially exposed population. An additional objective is to compare the results with those obtained with a more common approach that uses, as spatial units, basic census units, which are the best spatial data disaggregation and detailed information available for regional studies in Portugal. Considering the Portuguese census data and a layer of residential building footprint, which was used as ancillary information, the number of exposed inhabitants differs significantly according to the approach used. When the census unit approach is used, considering the three highest landslide susceptible classes, the number of exposed inhabitants is in general overestimated. Despite the associated uncertainties of a general cost–benefit analysis, the presented methodology seems to be a reliable approach for gaining a first approximation of a more detailed estimation of exposed people. The approach based on dasymetric cartography allows the spatial resolution of population over large areas to be increased and enables the use of detailed landslide susceptibility maps, which are valuable for improving the exposed population assessment.Copernicus PublicationsRepositório da Universidade de LisboaGarcia, Ricardo A COliveira, SérgioZêzere, José2017-06-21T09:51:30Z20162016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/28116eng1561-863310.5194/nhess-16-2769-2016info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-08T16:19:27Zoai:repositorio.ul.pt:10451/28116Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:44:21.711845Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Assessing population exposure for landslide risk analysis using dasymetric cartography |
title |
Assessing population exposure for landslide risk analysis using dasymetric cartography |
spellingShingle |
Assessing population exposure for landslide risk analysis using dasymetric cartography Garcia, Ricardo A C population exposure landslide risk analysis dasymetric cartography |
title_short |
Assessing population exposure for landslide risk analysis using dasymetric cartography |
title_full |
Assessing population exposure for landslide risk analysis using dasymetric cartography |
title_fullStr |
Assessing population exposure for landslide risk analysis using dasymetric cartography |
title_full_unstemmed |
Assessing population exposure for landslide risk analysis using dasymetric cartography |
title_sort |
Assessing population exposure for landslide risk analysis using dasymetric cartography |
author |
Garcia, Ricardo A C |
author_facet |
Garcia, Ricardo A C Oliveira, Sérgio Zêzere, José |
author_role |
author |
author2 |
Oliveira, Sérgio Zêzere, José |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Garcia, Ricardo A C Oliveira, Sérgio Zêzere, José |
dc.subject.por.fl_str_mv |
population exposure landslide risk analysis dasymetric cartography |
topic |
population exposure landslide risk analysis dasymetric cartography |
description |
Assessing the number and locations of exposed people is a crucial step in landslide risk management and emergency planning. The available population statistical data frequently have insufficient detail for an accurate assessment of potentially exposed people to hazardous events, mainly when they occur at the local scale, such as with landslides. The present study aims to apply dasymetric cartography to improving population spatial resolution and to assess the potentially exposed population. An additional objective is to compare the results with those obtained with a more common approach that uses, as spatial units, basic census units, which are the best spatial data disaggregation and detailed information available for regional studies in Portugal. Considering the Portuguese census data and a layer of residential building footprint, which was used as ancillary information, the number of exposed inhabitants differs significantly according to the approach used. When the census unit approach is used, considering the three highest landslide susceptible classes, the number of exposed inhabitants is in general overestimated. Despite the associated uncertainties of a general cost–benefit analysis, the presented methodology seems to be a reliable approach for gaining a first approximation of a more detailed estimation of exposed people. The approach based on dasymetric cartography allows the spatial resolution of population over large areas to be increased and enables the use of detailed landslide susceptibility maps, which are valuable for improving the exposed population assessment. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016 2016-01-01T00:00:00Z 2017-06-21T09:51:30Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10451/28116 |
url |
http://hdl.handle.net/10451/28116 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1561-8633 10.5194/nhess-16-2769-2016 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Copernicus Publications |
publisher.none.fl_str_mv |
Copernicus Publications |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799134364841279488 |