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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Detalles Bibliográficos
Autores principales: 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: Online Artículo Texto
Lenguaje:English
Publicado: 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615085/
https://www.ncbi.nlm.nih.gov/pubmed/37315611
http://dx.doi.org/10.1016/j.scitotenv.2023.164794

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615085/
https://www.ncbi.nlm.nih.gov/pubmed/37315611
http://dx.doi.org/10.1016/j.scitotenv.2023.164794

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