Morphological and Environmental Drivers of Urban Heat Islands: A Geospatial Model of Nighttime Land Surface Temperature in Iberian Cities

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.

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Publication Details

Journal
Applied Sciences
Published
2025-05-28
DOI
https://doi.org/10.3390/app15116093
Citations
2
Primary Topic
Urban Heat Island Mitigation
Type
article
Field-Weighted Citation Impact
1.60

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article

Morphological and Environmental Drivers of Urban Heat Islands: A Geospatial Model of Nighttime Land Surface Temperature in Iberian Cities

Saray Martínez-Lastras, Susana Del Pozo, José Antonio Martín-Jiménez, S. Lagüela et al.
2 citations
Applied Sciences
Urban Heat Island Mitigation
1.60
article

Morphological and Environmental Drivers of Urban Heat Islands: A Geospatial Model of Nighttime Land Surface Temperature in Iberian Cities

Saray Martínez-Lastras, Susana Del Pozo, José Antonio Martín-Jiménez, S. Lagüela, Gustavo Hernández-Herráez
article en
2 citations

Abstract

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.

Applied SciencesVol. 15(11)
Universidad de Salamanca (ES), Catholic University of Ávila (ES)
Ministerio de Ciencia, Innovación y Universidades
Openalex Percentile: Top 18%
Urban Heat Island Mitigation
1.60
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