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Torres Fernandez, Yolanda ORCID: https://orcid.org/0000-0003-1206-6536, Arranz Justel, Jose Juan
ORCID: https://orcid.org/0000-0003-1653-2020, Martinez Cuevas, Sandra
ORCID: https://orcid.org/0000-0002-2150-3251, Gaspar Escribano, Jorge Miguel
ORCID: https://orcid.org/0000-0002-2220-7112, Benito Oterino, Maria Belen
ORCID: https://orcid.org/0000-0003-3582-6438, Staller Vazquez, Alejandra
ORCID: https://orcid.org/0000-0003-0335-0949 and Gómez Doménech, Igor
(2019).
The new methods for rapid exposure and seismic vulnerability assessment. How do they adapt to different scenarios?.
"Proceedings, 2019, CIGeo 2019", v. 19
(n. 1);
pp. 14-17.
ISSN 2504-3900.
https://doi.org/10.3390/proceedings2019019014.
Title: | The new methods for rapid exposure and seismic vulnerability assessment. How do they adapt to different scenarios? |
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Author/s: |
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Item Type: | Article |
Título de Revista/Publicación: | Proceedings, 2019, CIGeo 2019 |
Date: | July 2019 |
ISSN: | 2504-3900 |
Volume: | 19 |
Subjects: | |
Freetext Keywords: | Exposure; Earthquake vulnerability; LiDAR; Orthophoto; Machine learning |
Faculty: | E.T.S.I. en Topografía, Geodesia y Cartografía (UPM) |
Department: | Ingeniería Topográfica y Cartografía |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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We present a procedure for exposure and vulnerability evaluation that integrates LiDAR, orthophotos, and other ancillary datasets. It comprises three phases: (1) city stratification into homogeneous regions; (2) exposure database compilation; and (3) vulnerability allocation using predictive modelling. We have conducted two applications in Lorca (Spain) and Port-au-Price (Haiti) and here we compare them. Each phase of the method is subject to variations due mainly to data availability; however, it does not affect the final accuracy that remains high in both scenarios (over 80%). It is a flexible procedure that is able to adapt to the particular features of two different cities.
Item ID: | 63883 |
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DC Identifier: | https://oa.upm.es/63883/ |
OAI Identifier: | oai:oa.upm.es:63883 |
DOI: | 10.3390/proceedings2019019014 |
Official URL: | https://eventos.upm.es/27154/detail/cigeo-2019.htm... |
Deposited by: | Memoria Investigacion |
Deposited on: | 04 Feb 2021 11:26 |
Last Modified: | 10 Feb 2021 15:08 |