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dc.contributor.authorHernández-Herráez, Gustavo
dc.contributor.authorMartínez Lastras, Saray 
dc.contributor.authorLagüela López, Susana 
dc.contributor.authorMartín Jiménez, José Antonio 
dc.contributor.authorPozo Aguilera, Susana del 
dc.date.accessioned2026-04-07T07:13:00Z
dc.date.available2026-04-07T07:13:00Z
dc.date.issued2025-05-28
dc.identifier.urihttp://hdl.handle.net/10366/170834
dc.description.abstract[EN] This study explores how urban morphological and environmental factors influence Urban Heat Islands (UHIs) using a geospatial modeling approach. The aim of the research is to develop a methodology to assess UHI effects, emphasizing the role of urban morphology, land use, and vegetation in nighttime heat accumulation. A micro-scale analysis with a 50 m resolution is conducted by integrating a custom QGIS plugin with open-access data, ensuring broad applicability. The 50 m resolution was chosen because it allows for the capture of local variations in UHI intensity while maintaining the scalability of the urban analysis across different city contexts. Non-parametric statistical analyses (ANOVA, Kruskal–Wallis H test, and correlation assessments) were used to evaluate the relationships between the urban parameters—wind corridors, altitude, vegetation (NDVI), surface water (NDWI), and the Sky View Factor (SVF)—and Nighttime Land Surface Temperature (LST). Given that UHI variations during summer, particularly in cities of the Iberian Peninsula, are closely linked to summer heat severity, this factor was considered to classify the cities for the study. Correlation analyses confirm that all tested factors influence LST, with wind corridors being the least significant. The model performance evaluation shows the highest errors in cities with lower summer severity (RMSE = 1.586 °C, MAE = 1.2686 °C, MAPE = 6.99%) and the best performance in warmer cities (RMSE = 1.4 °C, MAE = 1.14 °C, MAPE = 4.5%). Validation in four cities of the Iberian Peninsula confirmed the model’s reliability, with the worst RMSE value of 2.04 °C. These findings contribute to a better understanding of the factors driving UHIs and provide a scalable assessment framework.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacionales_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/es_ES
dc.subjectUrban heat islandes_ES
dc.subjectLand surface temperaturees_ES
dc.subjectBuildingses_ES
dc.subjectUrban morphologyes_ES
dc.subjectNDVIes_ES
dc.subjectNDWIes_ES
dc.subjectGeospatial analysises_ES
dc.subjectUrban planninges_ES
dc.titleMorphological and Environmental Drivers of Urban Heat Islands: A Geospatial Model of Nighttime Land Surface Temperature in Iberian Citieses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.identifier.doi10.3390/app15116093
dc.relation.projectIDMIA.2021.M01.0004.E24es_ES
dc.relation.projectIDFPU21/00446es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.essn2076-3417
dc.journal.titleApplied Scienceses_ES
dc.volume.number15es_ES
dc.issue.number11es_ES
dc.page.initial6093es_ES
dc.type.hasVersioninfo:eu-repo/semantics/updatedVersiones_ES


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