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dc.contributor.authorMaté González, Miguel Ángel 
dc.contributor.authorSáez Blázquez, Cristina 
dc.contributor.authorCamargo Vargas, Sergio Alejandro 
dc.contributor.authorHerranz Herranz, Daniel
dc.date.accessioned2026-09-01T10:33:59Z
dc.date.available2026-09-01T10:33:59Z
dc.date.issued2026
dc.identifier.urihttp://hdl.handle.net/10366/172641
dc.description.abstract[EN] Road infrastructures are fundamental for ensuring connectivity, safety, and the efficient functioning of transportation networks. However, extreme weather conditions, particularly low temperatures and ice formation, pose significant risks to user safety and road conditions. This research focuses on the development of a geospatial model designed to identify road sections exposed to these harsh weather conditions. The model integrates different sources of information, including meteorological and satellite data, topographic information, and road maintenance plans, through a consistent methodology for data processing and analysis. A combination of geospatial analysis and advanced processing techniques was employed to identify and map regions most vulnerable to the formation of ice. The results show good spatial agreement between the areas identified by the model and the available local information, supporting its ability to characterize areas with greater susceptibility to winter-related hazards. This work highlights the potential of the developed geospatial model to support the planning of preventive and maintenance measures on roads. By providing spatial information on susceptibility to low temperatures and ice formation, the model can serve as a decision-support tool for road management, contributing to the planning of targeted interventions and improved road safety. Overall, this study underscores the importance of integrating advanced geospatial techniques into infrastructure management to improve response strategies in the face of extreme weather events.es_ES
dc.language.isoenges_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/es_ES
dc.subjectgeospatial analysises_ES
dc.subjectroad infrastructurees_ES
dc.subjectextreme weather eventses_ES
dc.subjectGIS-based modeles_ES
dc.subjectice formationes_ES
dc.subjectinfrastructure managementes_ES
dc.titleGIS-Based Evaluation for Identifying Road Sections Vulnerable to Extreme Winter Weather Conditionses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.identifier.doi10.3390/app16157768
dc.relation.projectIDPID2022-142097OA-I00es_ES
dc.relation.projectIDRYC2021-034813-Ies_ES
dc.relation.projectIDRYC2021-034720-Ies_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.essn2076-3417
dc.journal.titleApplied Scienceses_ES
dc.volume.number16es_ES
dc.issue.number15es_ES
dc.page.initial7768es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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Attribution-NonCommercial-NoDerivatives 4.0 International
Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 International