No. 31 (2026): Risks and built environment: From knowledge to project
Research and Experimentation

Assessing urban heat island risk during heatwaves with satellite data and fuzzy clustering techniques

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  • Rosa Cafaro,
  • Barbara Cardone,
  • Ferdinando Di Martino
Rosa Cafaro
Dipartimento di Architettura, Università degli Studi di Napoli Federico II, Italia
Barbara Cardone
Dipartimento di Architettura, Università degli Studi di Napoli Federico II, Italia
Ferdinando Di Martino
Dipartimento di Architettura, Università degli Studi di Napoli Federico II, Italia
DOI: https://doi.org/10.36253/techne-18693

Published 2026-07-29

Keywords

  • Urban Heat Island,
  • Fuzzy C-Means,
  • Satellite indices,
  • Climate risk,
  • Urban resilience

How to Cite

Cafaro, R., Cardone, B., & Di Martino, F. (2026). Assessing urban heat island risk during heatwaves with satellite data and fuzzy clustering techniques. TECHNE - Journal of Technology for Architecture and Environment, (31), 231–244. https://doi.org/10.36253/techne-18693

Copyright (c) 2026 Rosa Cafaro, Barbara Cardone, Ferdinando Di Martino

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

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Abstract

This paper presents a methodology for mapping urban heat island risk generated by heat waves, based on Landsat 8 satellite data and unsupervised artificial intelligence classification techniques. The integration of the land surface temperature (LST) raster and the vegetation index (NDVI) allows the identification of urban areas with high thermal exposure (hot spots), the most resilient areas (cold spots), and the estimation of the resident population at risk. The tests were carried out on the city of Naples during heat waves that occurred in the last three years from 2022 to 2024. The results show that the proposed framework can provide an operational tool for decision makers to monitor heat islands and plan climate-proof solutions in the most critical urban contexts. The proposed methodology is portable and transferable to other urban contexts.

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