A machine learning approach for mapping surface urban heat island using environmental and socioeconomic variables: a case study in a medium-sized Brazilian city

Smart cities must deal with climate change and find solutions to mitigate phenomena such as urban heat islands (UHI). The land surface temperature (LST) extracted from thermal images is a primary source of information to study UHI, characterizing the surface urban heat islands (SUHI). In addition to...

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Veröffentlicht in:	Environmental earth sciences 2023-07, Vol.82 (13), p.325-325, Article 325
Hauptverfasser:	Furuya, Michelle Taís Garcia, Furuya, Danielle Elis Garcia, de Oliveira, Lucas Yuri Dutra, da Silva, Paulo Antonio, Cicerelli, Rejane Ennes, Gonçalves, Wesley Nunes, Junior, José Marcato, Osco, Lucas Prado, Ramos, Ana Paula Marques
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Biogeosciences case studies Climate change Construction planning decision support systems Decision trees Demographic variables Earth and Environmental Science Earth Sciences Environmental Science and Engineering Geochemistry Geology Heat heat island Hydrology/Water Resources information sources Islands Land surface temperature Landsat Learning algorithms Machine learning Original Article prediction Remote sensing Satellite imagery Smart cities Social factors Socioeconomic factors Socioeconomics Surface temperature Terrestrial Pollution Thermal imaging Urban heat islands Urban planning
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