AI-Driven Solutions for Predicting and Mitigating Urban Heat Islands

Urban heat islands (UHIs) represent a significant challenge in urban sustainability. This study explores AI-driven methodologies for predicting and mitigating UHIs by leveraging real-time data and machine learning algorithms. Our findings indicate that AI offers precise predictive modeling and effective intervention strategies to reduce urban temperatures.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-03
DOI
https://doi.org/10.5281/zenodo.14269391
Primary Topic
Urban Heat Island Mitigation
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Driven Solutions for Predicting and Mitigating Urban Heat Islands

Zenodo (CERN European Organization for Nuclear Research)
Urban Heat Island Mitigation
article

AI-Driven Solutions for Predicting and Mitigating Urban Heat Islands

article en

Abstract

Urban heat islands (UHIs) represent a significant challenge in urban sustainability. This study explores AI-driven methodologies for predicting and mitigating UHIs by leveraging real-time data and machine learning algorithms. Our findings indicate that AI offers precise predictive modeling and effective intervention strategies to reduce urban temperatures.

Zenodo (CERN European Organization for Nuclear Research)
King Abdullah University of Science and Technology (SA)
Sustainable cities and communities
Openalex Percentile: Top 64%
Urban Heat Island Mitigation
DOIOpen Access PDFOpenAlex
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AI-Driven Solutions for Predicting and Mitigating Urban Heat Islands · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS