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20172026
most citedSpatial Structure of City Population Growth

68 citations · 265 across the 47 of their papers we have counts for

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Showing physics.soc-phShow all

12 papers · 1 filter

physics.soc-ph2022★ 68 cited

Spatial Structure of City Population Growth

Sandro M. Reia, P. Suresh C. Rao, Marc Barthelemy +1

We show here that population growth, resolved at the county level, is spatially heterogeneous both among and within the U.S. metropolitan statistical areas. Our analysis of data fo…

physics.soc-ph2021★ 6 cited

Mobile Phone Location Data for Disasters: A Review from Natural Hazards and Epidemics

Takahiro Yabe, Nicholas K W Jones, P Suresh C Rao +2

Rapid urbanization and climate change trends are intertwined with complex interactions of various social, economic, and political factors. The increased trends of disaster risks ha…

physics.soc-ph2021★ 5 cited

Location Data Reveals Disproportionate Disaster Impact Amongst the Poor: A Case Study of the 2017 Puebla Earthquake Using Mobilkit

Takahiro Yabe, Nicholas K W Jones, Nancy Lozano-Gracia +4

Location data obtained from smartphones is increasingly finding use cases in disaster risk management. Where traditionally, CDR has provided the predominant digital footprint for h…

physics.soc-ph2021

Spatiotemporal impacts of human activities and socio-demographics during the COVID-19 outbreak in the U.S

Lu Ling, Xinwu Qian, Satish V. Ukkusuri +1

Understanding influencing factors is essential for the surveillance and prevention of infectious diseases, and the factors are likely to vary spatially and temporally as the diseas…

physics.soc-ph2021★ 7 cited

Resilience of Interdependent Urban Socio-Physical Systems using Large-Scale Mobility Data: Modeling Recovery Dynamics

Takahiro Yabe, P. Suresh C. Rao, Satish V. Ukkusuri

Cities are complex systems comprised of socioeconomic systems relying on critical services delivered by multiple physical infrastructure networks. Due to interdependencies between…

physics.soc-ph2021★ 2 cited

Quantifying Spatial Homogeneity of Urban Road Networks via Graph Neural Networks

Jiawei Xue, Nan Jiang, Senwei Liang +4

Quantifying the topological similarities of different parts of urban road networks (URNs) enables us to understand the urban growth patterns. While conventional statistics provide…