TY - JOUR
T1 - Urban spatial dynamic modeling based on urban amenity data to inform smart city planning
AU - Cai, Zipan
AU - Kwak, Yoonshin
AU - Cvetkovic, Vladimir
AU - Deal, Brian
AU - Mörtberg, Ulla
N1 - We gratefully acknowledge the financial support provided by Stockholm County Council , SLL dnr LS 2018-0736 . We are grateful to Tillväxt- och Regionplaneförvaltningen (TRF) for granting us access to the regional development plan document data - Regional Utvecklingsplan För Stockholmsregionen (RUFS) 2050. The project Humanizing the Sustainable Smart City (HiSS) within the KTH Digital Futures research program, has partially supported ZC and VC for this research.
We gratefully acknowledge the financial support provided by Stockholm County Council, SLL dnr LS 2018-0736. We are grateful to Tillväxt- och Regionplaneförvaltningen (TRF) for granting us access to the regional development plan document data - Regional Utvecklingsplan För Stockholmsregionen (RUFS) 2050. The project Humanizing the Sustainable Smart City (HiSS) within the KTH Digital Futures research program, has partially supported ZC and VC for this research.
PY - 2023/6
Y1 - 2023/6
N2 - An ideal form of smart city planning would focus on the availability of urban amenities that can meet the basic needs of a resident's material life, civil connections, and humanistic spirit. Previous studies have concentrated on analyzing the spatial distribution of urban services, with less attention on their contribution as local urban amenities. In this study, we propose a spatial dynamic modeling approach based on urban amenities using social media data from Google Place API to provide locational information on potential resident interactions. We use a representative region in Europe (Stockholm County, SE) to simulate and project urban development in the region until 2050. Our circular conceptual framework of spatial information and feedback supports decision-makers in testing possible urban planning scenarios that align with the vision of a smart city. Simulation results reveal the interplay between human-land interactions on a specific spatial-temporal scale, and we analyze scenario outcomes in relation to commercial and residential land uses. Overall, our study provides a new perspective on human-social behavior-driven urban development, through a smart, spatial dynamic model as a planning support system that can enhance realism, and ultimately help realize planned development objectives in the region.
AB - An ideal form of smart city planning would focus on the availability of urban amenities that can meet the basic needs of a resident's material life, civil connections, and humanistic spirit. Previous studies have concentrated on analyzing the spatial distribution of urban services, with less attention on their contribution as local urban amenities. In this study, we propose a spatial dynamic modeling approach based on urban amenities using social media data from Google Place API to provide locational information on potential resident interactions. We use a representative region in Europe (Stockholm County, SE) to simulate and project urban development in the region until 2050. Our circular conceptual framework of spatial information and feedback supports decision-makers in testing possible urban planning scenarios that align with the vision of a smart city. Simulation results reveal the interplay between human-land interactions on a specific spatial-temporal scale, and we analyze scenario outcomes in relation to commercial and residential land uses. Overall, our study provides a new perspective on human-social behavior-driven urban development, through a smart, spatial dynamic model as a planning support system that can enhance realism, and ultimately help realize planned development objectives in the region.
KW - Human-land interaction
KW - Human-social behavior
KW - Planning support system
KW - Smart city
KW - Spatial dynamic model
KW - Urban amenities
KW - Urban planning
UR - http://www.scopus.com/inward/record.url?scp=85160678432&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85160678432&partnerID=8YFLogxK
U2 - 10.1016/j.ancene.2023.100387
DO - 10.1016/j.ancene.2023.100387
M3 - Article
AN - SCOPUS:85160678432
SN - 2213-3054
VL - 42
JO - Anthropocene
JF - Anthropocene
M1 - 100387
ER -