Phenotyping urban built and natural environments with high-resolution satellite images and unsupervised deep learning

Cities in the developing world are expanding rapidly, and undergoing changes to their roads, buildings, vegetation, and other land use characteristics. Timely data are needed to ensure that urban change enhances health, wellbeing and sustainability. We present and evaluate a novel unsupervised deep...

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Detalhes bibliográficos
Publicado no:Sci Total Environ
Main Authors: Metzler, A Barbara, Nathvani, Ricky, Sharmanska, Viktoriia, Bai, Wenjia, Muller, Emily, Moulds, Simon, Agyei-Asabere, Charles, Adjei-Boadi, Dina, Kyere-Gyeabour, Elvis, Tetteh, Jacob Doku, Owusu, George, Agyei-Mensah, Samuel, Baumgartner, Jill, Robinson, Brian E, Arku, Raphael E, Ezzati, Majid
Formato: Artigo
Idioma:Inglês
Publicado em: 2023
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7615085/
https://ncbi.nlm.nih.gov/pubmed/37315611
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.scitotenv.2023.164794
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