URSUS_UHI: URban SUStainability software for detection of unfavourable areas due to the Urban Heat Island effect

URSUS_UHI: URban SUStainability software for detection of unfavourable areas due to the Urban Heat Island effect

Authors

Francisco Rodríguez-Gómez , José del Campo-Ávila , Domingo López-Rodríguez , Luis Pérez-Urrestarazu

Published

1 February 2025

Publication details

SoftwareX vol. 29 , pages 101997.

Links

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Abstract

Identifying the most unfavourable areas of cities, in terms of high temperatures and lack of vegetation, can help to improve urban sustainability and combat climate change. URSUS_UHI is a software that could help make decisions on which areas need priority attention in terms of adding green infrastructure to reduce temperatures. It develops a spatial data mining processes that incorporates expert knowledge to automatically detect the most disadvantaged areas in terms of higher temperatures and lack of vegetation. In this way, users such as urban planners or landscape engineers can identify the most suitable areas in which to act.

Funding

NoteProjects funding this work

Citation

How to cite

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 (2025), p. 101997. ISSN: 2352-7110. DOI: https://doi.org/10.1016/j.softx.2024.101997. URL: https://www.sciencedirect.com/science/article/pii/S2352711024003674.

BibTeX

<pre><code>

@article{RODRIGUEZGOMEZ2025101997, title = {URSUS_UHI: URban SUStainability software for detection of unfavourable areas due to the Urban Heat Island effect}, journal = {SoftwareX}, volume = {29}, pages = {101997}, year = {2025}, issn = {2352-7110}, doi = {https://doi.org/10.1016/j.softx.2024.101997}, url = {https://www.sciencedirect.com/science/article/pii/S2352711024003674}, author = {Francisco Rodríguez-Gómez and José {del Campo-Ávila} and Domingo López-Rodríguez and Luis Pérez-Urrestarazu}, keywords = {Remote sensing, Disadvantaged area index (DAI), Spatial data mining, Intelligent decision support system}, abstract = {Identifying the most unfavourable areas of cities, in terms of high temperatures and lack of vegetation, can help to improve urban sustainability and combat climate change. URSUS_UHI is a software that could help make decisions on which areas need priority attention in terms of adding green infrastructure to reduce temperatures. It develops a spatial data mining processes that incorporates expert knowledge to automatically detect the most disadvantaged areas in terms of higher temperatures and lack of vegetation. In this way, users such as urban planners or landscape engineers can identify the most suitable areas in which to act.} }

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URSUS_UHI: URban SUStainability software for detection of unfavourable areas due to the Urban Heat Island effect

Cites

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Papers citing this work

The following is a non-exhaustive list of papers that cite this work:

1. Venkata Sudhakar Chowdam, Venkata Naresh M, Ganjikunta Ganesh Kumar, et al. (2026). Remote sensing and machine learning approaches for heat island mapping and analysis: a review and framework for sustainable smart cities. Environment Development and Sustainability DOI
2. Ji-Sun Ko, Juwon Kim, Dongha Kim, et al. (2025). Applications of Data-Driven Approaches Using Artificial Intelligence Algorithms and Quantum Computing in Sustainability. DOI