Work

Measuring spatio-temporal accessibility to emergency medical services through big GPS data

Year: 2019

Type: article

Source: Health & Place

DOI: 10.1016/j.healthplace.2019.01.012

Authors: Tianqi Xia, Xuan Song, Haoran Zhang, Xiaoya Song, Hiroshi Kanasugi, Ryosuke Shibasaki

Institutions: Artificial Intelligence Research Center, Center for Spatial Information Science, The University of Tokyo, National Institute of Advanced Industrial Science and Technology, The University of Tokyo, Harbin Institute of Technology

Language: English

Topic: Facility Location and Emergency Management

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Sustainable cities and communities, Good health and well-being, Reduced inequalities

Open Access status: bronze

Funders: Ministry of Education, Culture, Sports, Science and Technology, Japan Society for the Promotion of Science, Japan Science and Technology Agency, Strategic International Collaborative Research Program

Awards: G6893544582, DeepMob: Learning Deep Models from Big and Heterogeneous Data for Next-generation Urban Emergency Management, Fusion of sensing and simulation of tsunami damage assessment towards innovation of disaster medical system

OpenAlex ID: W2913630279

FWCI: 20.35

Cites: 43

Cited by: 129

Related to: 10