Cargando…
Spatial and deep learning analyses of urban recovery from the impacts of COVID-19
This study investigates urban recovery from the COVID-19 pandemic by focusing on three main types of working, commercial, and night-life activities and associating them with land use and inherent socio-economic patterns as well as points of interests (POIs). Massive multi-source and multi-scale data...
Autores principales: | Ma, Shuang, Li, Shuangjin, Zhang, Junyi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9922321/ https://www.ncbi.nlm.nih.gov/pubmed/36774395 http://dx.doi.org/10.1038/s41598-023-29189-5 |
Ejemplares similares
-
Association of built environment attributes with the spread of COVID-19 at its initial stage in China
por: Li, Shuangjin, et al.
Publicado: (2021) -
Diverse and nonlinear influences of built environment factors on COVID-19 spread across townships in China at its initial stage
por: Ma, Shuang, et al.
Publicado: (2021) -
“What should be computed” for supporting post-pandemic recovery policymaking? A life-oriented perspective
por: Zhang, Junyi, et al.
Publicado: (2021) -
Effects of transport-related COVID-19 policy measures: A case study of six developed countries
por: Zhang, Junyi, et al.
Publicado: (2021) -
The impacts of spatial resolutions on global urban-related change analyses and modeling
por: Li, Xia, et al.
Publicado: (2022)