Assessment of the October 2024 cut-off low event floods impact in Valencia (Spain) with satellite and geospatial data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985530%3A_____%2F25%3A00637557" target="_blank" >RIV/67985530:_____/25:00637557 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2072-4292/17/13/2145" target="_blank" >https://www.mdpi.com/2072-4292/17/13/2145</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/rs17132145" target="_blank" >10.3390/rs17132145</a>
Alternative languages
Result language
angličtina
Original language name
Assessment of the October 2024 cut-off low event floods impact in Valencia (Spain) with satellite and geospatial data
Original language description
The October 2024 cut-off low event triggered one of the most catastrophic floods recorded in the Valencia Metropolitan Area, exposing significant vulnerabilities in urban planning, infrastructure resilience, and emergency preparedness. This study presents a novel comprehensive assessment of the event, using a multi-sensor satellite approach combined with socio-economic and infrastructure data at the metropolitan scale. It provides a comprehensive spatial assessment of the flood's impacts by integrating of radar Sentinel-1 and optical Sentinel-2 and Landsat 8 imagery with datasets including population density, land use, and critical infrastructure layers. Approximately 199 km2 were inundated, directly affecting over 90,000 residents and compromising vital infrastructure such as hospitals, schools, transportation corridors, and agricultural lands. Results highlight the exposure of peri-urban zones and agricultural areas, reflecting the socio-economic risks associated with the rapid urban expansion into flood-prone plains. The applied methodology demonstrates the essential role of multi-sensor remote sensing in accurately delineating flood extents and assessing socio-economic impacts. This approach constitutes a transferable framework for enhancing disaster risk management strategies in other Mediterranean urban regions. As extreme hydrometeorological events become more frequent under changing climatic conditions, the findings underscore the urgent need for integrating remote sensing technologies, early warning systems, and nature-based solutions into regional governance to strengthen resilience, reduce vulnerabilities, and mitigate future flood risks.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10507 - Volcanology
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Remote Sensing
ISSN
2072-4292
e-ISSN
2072-4292
Volume of the periodical
17
Issue of the periodical within the volume
13
Country of publishing house
CH - SWITZERLAND
Number of pages
31
Pages from-to
2145
UT code for WoS article
001526309500001
EID of the result in the Scopus database
2-s2.0-105010561145