GIS-based Spatial and Temporal Analysis of Aging-Involved Accidents: a Case Study of Three Counties in Florida

Roadway accidents claim more than 30,000 lives each year in the United States, and they continue adversely affecting people’s well-being. This problem becomes even more challenging when aging populations are considered due to their vulnerability to accidents. This is especially a major concern in Fl...

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Bibliographic Details
Published in:Applied spatial analysis and policy 2017-12, Vol.10 (4), p.537-563
Main Authors: Vemulapalli, Sai Saylesh, Ulak, Mehmet Baran, Ozguven, Eren Erman, Sando, Thobias, Horner, Mark W., Abdelrazig, Yassir, Moses, Ren
Format: Article
Language:English
Subjects:
Accidents
Aging
Automobiles
Case studies
Geographic information systems
Human Geography
Landscape/Regional and Urban Planning
Older people
Population growth
Regional/Spatial Science
Social Sciences
Spatial analysis
Traffic accidents & safety
Transportation planning
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Summary:Roadway accidents claim more than 30,000 lives each year in the United States, and they continue adversely affecting people’s well-being. This problem becomes even more challenging when aging populations are considered due to their vulnerability to accidents. This is especially a major concern in Florida since the accident risk is increasing proportionally to the population growth of aging Floridians. This study investigates the spatial and temporal patterns of aging people-involved accidents using geographical information systems (GIS)-based methods via a case study of three urban counties in Florida, selected based on their high aging-involved accident rates. A series of spatial analytic methods are utilized to explore accident patterns, including a network distance-based kernel density estimation method, which provides an unbiased distribution of the accidents over the local roadways. An accident density ratio measure is also developed in order to understand how accidents involving aging people occur at different locations than those of the general population. Results indicate that high risk locations for aging-involved accidents show different spatial and temporal patterns than those for other age groups. Investigating these distinct patterns at a high spatio-temporal scale can lead to better aging-focused transportation plans and policies.
ISSN:1874-463X
1874-4621
DOI:10.1007/s12061-016-9192-4