Detection of unfavourable urban areas with higher temperatures and lack of green spaces using satellite imagery in sixteen Spanish cities
Abstract
This paper seeks to identify the most unfavourable areas of a city in terms of high temperatures and the absence of green infrastructure. An automatic methodology based on remote sensing and data analysis has been developed and applied in sixteen Spanish cities with different characteristics. Landsat-8 satellite images were selected for each city from the July-August period of 2019 and 2020 to calculate the spatial variation of land surface temperature (LST). The Normalized Difference Vegetation Index (NDVI) was used to determine the abundance of vegetation across the city. Based on the NDVI and LST maps created, a k-means unsupervised classification clustering was performed to automatically identify the different clusters according to how favourable these areas were in terms of temperature and presence of vegetation. A Disadvantaged Area Index (DAI), combining both variables, was developed to produce a map showing the most unfavourable areas for each city. Overall, the percentage of the area susceptible to improvement with more vegetation in the cities studied ranged from 13 % in Huesca to 64–65 % in Bilbao and Valencia. The influence of several factors, such as the presence of water bodies or large buildings, is discussed. Detecting unfavourable areas is a very interesting tool for defining future planning strategy for green spaces.
Funding
URSUS-DM: Nuevos desarrollos en minería de datos para su utilización en la sostenibilidad urbana
Citation
Please, cite this work as:
[Rod+22] F. Rodríguez-Gómez, R. Fernández-Cañero, G. Pérez, et al. “Detection of unfavourable urban areas with higher temperatures and lack of green spaces using satellite imagery in sixteen Spanish cities”. In: Urban Forestry & Urban Greening 78 (2022), p. 127783. ISSN: 1618-8667. DOI: https://doi.org/10.1016/j.ufug.2022.127783. URL: https://www.sciencedirect.com/science/article/pii/S1618866722003260.
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Papers citing this work
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[1] A. Ali, B. Hussain, R. U. Hissan, et al. “Examining the landscape transformation and temperature dynamics in Pakistan”. In: Scientific Reports 15.1 (Jan. 2025). ISSN: 2045-2322. DOI: 10.1038/s41598-024-80323-3. URL: http://dx.doi.org/10.1038/s41598-024-80323-3.
[2] C. Aznarez, S. Kumar, A. Marquez-Torres, et al. “Ecosystem service mismatches evidence inequalities in urban heat vulnerability”. In: Science of The Total Environment 922 (Apr. 2024), p. 171215. ISSN: 0048-9697. DOI: 10.1016/j.scitotenv.2024.171215. URL: http://dx.doi.org/10.1016/j.scitotenv.2024.171215.
[3] M. J. Delgado-Capel, P. Cariñanos, and M. Escudero-Viñolo. “Capacity of Urban Green Infrastructure Spaces to Ameliorate Heat Wave Impacts in Mediterranean Compact Cities: Case Study of Granada (South-Eastern Spain)”. In: Land 12.5 (May. 2023), p. 1076. ISSN: 2073-445X. DOI: 10.3390/land12051076. URL: http://dx.doi.org/10.3390/land12051076.
[4] A. Marquez-Torres, S. Kumar, C. Aznarez, et al. “Assessing the cooling potential of green and blue infrastructure from twelve US cities with contrasting climate conditions”. In: Urban Forestry & Urban Greening 104 (Feb. 2025), p. 128660. ISSN: 1618-8667. DOI: 10.1016/j.ufug.2024.128660. URL: http://dx.doi.org/10.1016/j.ufug.2024.128660.
[5] P. K. Patra, D. Behera, V. Chettry, et al. “Geospatial analysis of unplanned urbanization: impact on land surface temperature and habitat suitability in Cuttack, India”. In: Discover Sustainability 6.1 (Feb. 2025). ISSN: 2662-9984. DOI: 10.1007/s43621-025-00920-8. URL: http://dx.doi.org/10.1007/s43621-025-00920-8.
[6] F. Rodríguez-Gómez, J. del Campo-Ávila, D. López-Rodríguez, et al. “URSUS_UHI: URban SUStainability software for detection of unfavourable areas due to the Urban Heat Island effect”. In: SoftwareX 29 (Feb. 2025), p. 101997. ISSN: 2352-7110. DOI: 10.1016/j.softx.2024.101997. URL: http://dx.doi.org/10.1016/j.softx.2024.101997.
[7] F. Rodríguez-Gómez, J. del Campo-Ávila, L. Pérez-Urrestarazu, et al. “URSUS_LST: URban SUStainability intelligent system for predicting the impact of urban green infrastructure on land surface temperatures”. In: Environmental Modelling & Software 186 (Mar. 2025), p. 106364. ISSN: 1364-8152. DOI: 10.1016/j.envsoft.2025.106364. URL: http://dx.doi.org/10.1016/j.envsoft.2025.106364.
[8] D. Saxena, M. Choudhary, and G. Sharma. “Land use and land cover change impact on characteristics of surface evapotranspiration in semi-arid environment of Western Rajasthan, India”. In: Water Practice & Technology 19.1 (Dec. 2023), p. 154–169. ISSN: 1751-231X. DOI: 10.2166/wpt.2023.222. URL: http://dx.doi.org/10.2166/wpt.2023.222.
[9] U. Sokolenko, Y. Honcharenko, and N. Oleksiichenko. “The Use of GIS Technologies for the Analysis and Monitoring of Green Infrastructure in Kharkiv, Ukraine”. In: Smart Technologies in Urban Engineering. Springer Nature Switzerland, 2023, p. 89–97. ISBN: 9783031468773. DOI: 10.1007/978-3-031-46877-3_8. URL: http://dx.doi.org/10.1007/978-3-031-46877-3_8.