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dc.contributor.authorAldao Pensado, Enrique 
dc.contributor.authorVeiga Piñeiro, Gonzalo 
dc.contributor.authorDomínguez Estévez, Pablo 
dc.contributor.authorVeiga López, Fernando 
dc.contributor.authorFontenla Carrera, Gabriel 
dc.contributor.authorGonzález Jorge, Higinio
dc.contributor.authorMartín Ortega, Elena Beatriz 
dc.date.accessioned2024-07-19T10:11:26Z
dc.date.available2024-07-19T10:11:26Z
dc.date.issued2024-06-27
dc.identifier.citationISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences, X-4/W5-2024, 1-7 (2024)spa
dc.identifier.issn21949050
dc.identifier.urihttp://hdl.handle.net/11093/7221
dc.description.abstractAbstract. Advanced Air Mobility (AAM) is an emerging sector that aims to optimise transportation in urban and interurban environments using Unmanned Aerial Vehicles (UAVs). However, these aircraft are particularly susceptible to adverse weather phenomena, such as turbulence or wind gusts. To ensure the safety of operations, high-resolution real-time atmospheric prediction models, such as those based on Computational Fluid Dynamics (CFD), are required. The development of these systems faces challenges as accurate geometric models of navigation environments are needed to simulate the interaction between the wind and the terrain and infrastructure. These models feature complex geometries, so they cannot be manually crafted, requiring automated processing of geospatial data sources. As the main novelty, this work presents a methodology for the automated modelling of interurban environments for CFD simulations using digital elevation models and georeferenced surface semantic classification data. A practical case study was developed in the outskirts of Vigo (Spain), where we demonstrate the effectiveness of our approach and its integration with the open-source CFD software OpenFOAM.en
dc.description.sponsorshipAgencia Estatal de Investigación | Ref. TED2021-129757B-C3spa
dc.description.sponsorshipAgencia Estatal de Investigación | Ref. PID2021-125060OB-100spa
dc.description.sponsorshipMinisterio de Universidades | Ref.FPU21/01176spa
dc.language.isoengspa
dc.publisherISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciencesspa
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-125060OB-I00/ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/TED2021-129756B-C31/ES/
dc.relationnfo:eu-repo/grantAgreement/MU//FPU21%2F01176
dc.rightsATTRIBUTION 4.0 INTERNATIONAL
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleTowards enhancing the safety of Advanced Air Mobility: Automatic 3D inter-urban modelling for improved weather monitoringen
dc.typearticlespa
dc.rights.accessRightsopenAccessspa
dc.identifier.doi10.5194/isprs-annals-X-4-W5-2024-1-2024
dc.identifier.editorhttps://isprs-annals.copernicus.org/articles/X-4-W5-2024/1/2024/spa
dc.publisher.departamentoEnxeñaría dos recursos naturais e medio ambientespa
dc.publisher.departamentoEnxeñaría mecánica, máquinas e motores térmicos e fluídosspa
dc.publisher.grupoinvestigacionLaboratorio de Sistemas Aeroespaciais e de Transportespa
dc.publisher.grupoinvestigacionEnxeñería Química, Térmica e Medioambientalspa
dc.subject.unesco3301 Ingeniería y Tecnología Aeronáuticasspa
dc.subject.unesco2509.99 Otrasspa
dc.date.updated2024-07-05T08:48:05Z
dc.computerCitationpub_title=ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences|volume=X-4/W5-2024|journal_number=|start_pag=1|end_pag=7spa


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    ATTRIBUTION 4.0 INTERNATIONAL
    Except where otherwise noted, this item's license is described as ATTRIBUTION 4.0 INTERNATIONAL