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https://doi.org/10.1016/j.apgeog.2022.102683
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Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Pérez Morales, Alfredo | - |
dc.contributor.author | Gil Guirado, Salvador | - |
dc.contributor.author | Martínez García, Víctor | - |
dc.date.accessioned | 2024-01-25T13:37:16Z | - |
dc.date.available | 2024-01-25T13:37:16Z | - |
dc.date.issued | 2022-03-25 | - |
dc.identifier.citation | Applied Geography. Volume 142, May 2022, 102683 | es |
dc.identifier.uri | http://hdl.handle.net/10201/137780 | - |
dc.description | 228/© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/ | es |
dc.description.abstract | Population disaggregation methods are a land management tool that is necessary to robustly assess the exposure of populations to natural hazards. The aim of these methods is to translate population values from large spatial units to smaller spatial units. Due to their improvement, the accuracy in quantifying the population exposed to natural hazards has increased significantly in recent years. However, in the case of floods, where the actual exposure to the hazard depends on the height of the buildings, there is a methodological deficiency with regard to reaching the necessary level of detail. This is a methodological challenge that is exacerbated in urban areas specialising in tourism, where there are a large number of dwellings dedicated to the housing of tourists. In this paper we propose a 3D cartographic dasymetry (DDF) method that, based on cadastral information and the population and housing census, manages to solve these problems of flood hazard exposure assessment reasonably well. For validation, the results are compared with three widely used 2D methods. Our work shows that the proposed method offers better outputs for use in high-precision work; but also, when such detail is not necessary, more basic methods achieve results with only marginal differences. | es |
dc.format | application/pdf | es |
dc.language | eng | es |
dc.publisher | Elsevier | es |
dc.relation | This work was supported by the Fundaci ́on S ́eneca - Agencia de Ciencia y Tecnología de la Regi ́on de Murcia, Spain (20912/PI/18) and the Spanish Ministry of Science and Innovation - Agencia Estatal de Investigaci ́on project (PID2020-114576RB-I00 - AgriCambio). Víctor Martínez-García acknowledges the financial support from the Spanish Ministry of Education and Personal Training (FPU19/05143). Salvador Gil-Guirado acknowledges the support and the ECCE project (PID2020- 115693RB-I00) of Ministerio de Ciencia e Innovaci ́on/Agencia Estatal de Investigaci ́on (MCIN/AEI/10.13039/501100011033/) | es |
dc.rights | info:eu-repo/semantics/openAccess | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Dasymetric mapping | es |
dc.subject | Cadastral | es |
dc.subject | Population mapping | es |
dc.subject | 3D mapping | es |
dc.subject | Flood exposure | es |
dc.subject | Flood hazard | es |
dc.subject | Touristic cities | es |
dc.subject.other | CDU::9 - Geografía e historia::91 - Geografía.Exploración de la tierra y de los distintos países.Viajes.Geografía regional | es |
dc.title | Dasymetry Dash Flood (DDF). A method for population mapping and flood exposure assessment in touristic citie | es |
dc.type | info:eu-repo/semantics/article | es |
dc.identifier.doi | https://doi.org/10.1016/j.apgeog.2022.102683 | - |
Aparece en las colecciones: | Artículos: Geografía |
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