Deep learning-based urban morphology for city-scale environmental modeling

Herein, we introduce a novel methodology to generate urban morphometric parameters that takes advantage of deep neural networks and inverse modeling. We take the example of Chicago, USA, where the Urban Canopy Parameters (UCPs) available from the National Urban Database and Access Portal Tool (NUDAP...

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Detalles Bibliográficos
Autores principales: Patel, Pratiman, Kalyanam, Rajesh, He, Liu, Aliaga, Daniel, Niyogi, Dev
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Physical Sciences and Engineering
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10003744/
https://www.ncbi.nlm.nih.gov/pubmed/36909824
http://dx.doi.org/10.1093/pnasnexus/pgad027

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10003744/
https://www.ncbi.nlm.nih.gov/pubmed/36909824
http://dx.doi.org/10.1093/pnasnexus/pgad027

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