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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Publicat a:Sci Total Environ
Autors principals: 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
Format: Artigo
Idioma:Inglês
Publicat: 2023
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Article
Accés en línia: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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