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      Spatiotemporal characteristics of elderly population’s traffic accidents in Seoul using space-time cube and space-time kernel density estimation

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      PLoS ONE
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          Abstract

          The purpose of this study is to analyze how the spatiotemporal characteristics of traffic accidents involving the elderly population in Seoul are changing by time period. We applied kernel density estimation and hotspot analyses to analyze the spatial characteristics of elderly people’s traffic accidents, and the space-time cube, emerging hotspot, and space-time kernel density estimation analyses to analyze the spatiotemporal characteristics. In addition, we analyzed elderly people’s traffic accidents by dividing cases into those in which the drivers were elderly people and those in which elderly people were victims of traffic accidents, and used the traffic accidents data in Seoul for 2013 for analysis. The main findings were as follows: (1) the hotspots for elderly people’s traffic accidents differed according to whether they were drivers or victims. (2) The hourly analysis showed that the hotspots for elderly drivers’ traffic accidents are in specific areas north of the Han River during the period from morning to afternoon, whereas the hotspots for elderly victims are distributed over a wide area from daytime to evening. (3) Monthly analysis showed that the hotspots are weak during winter and summer, whereas they are strong in the hiking and climbing areas in Seoul during spring and fall. Further, elderly victims’ hotspots are more sporadic than elderly drivers’ hotspots. (4) The analysis for the entire period of 2013 indicates that traffic accidents involving elderly people are increasing in specific areas on the north side of the Han River. We expect the results of this study to aid in reducing the number of traffic accidents involving elderly people in the future.

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          Most cited references33

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          The Analysis of Spatial Association by Use of Distance Statistics

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            Kernel Density Estimation of traffic accidents in a network space

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              Kernel density estimation and K-means clustering to profile road accident hotspots.

              Identifying road accident hotspots is a key role in determining effective strategies for the reduction of high density areas of accidents. This paper presents (1) a methodology using Geographical Information Systems (GIS) and Kernel Density Estimation to study the spatial patterns of injury related road accidents in London, UK and (2) a clustering methodology using environmental data and results from the first section in order to create a classification of road accident hotspots. The use of this methodology will be illustrated using the London area in the UK. Road accident data collected by the Metropolitan Police from 1999 to 2003 was used. A kernel density estimation map was created and subsequently disaggregated by cell density to create a basic spatial unit of an accident hotspot. Appended environmental data was then added to the hotspot cells and using K-means clustering, an outcome of similar hotspots was deciphered. Five groups and 15 clusters were created based on collision and attribute data. These clusters are discussed and evaluated according to their robustness and potential uses in road safety campaigning.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: Visualization
                Role: Data curationRole: Software
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                16 May 2018
                2018
                : 13
                : 5
                : e0196845
                Affiliations
                [001]Department of Social Studies, College of Education, Ewha Womans University, Seoul, South Korea
                Beihang University, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-0162-0645
                Article
                PONE-D-17-42102
                10.1371/journal.pone.0196845
                5955513
                29768453
                7ac687f8-620c-40a8-9587-eec7d0be5971
                © 2018 Kang et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 30 November 2017
                : 20 April 2018
                Page count
                Figures: 11, Tables: 0, Pages: 17
                Funding
                Funded by: This research was supported by the National Land Space Information Research Program funded by the Ministry of Land, Infrastructure and Transport of the Korean government
                Award ID: Grant No. 14NSIP-B080144-01
                Award Recipient :
                This research was supported by the National Land Space Information Research Program funded by the Ministry of Land, Infrastructure and Transport of the Korean government (Grant No. 14NSIP-B080144-01) (Receiver of fund: Youngok Kang). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Public and Occupational Health
                Traumatic Injury Risk Factors
                Road Traffic Collisions
                People and Places
                Population Groupings
                Age Groups
                Elderly
                Computer and Information Sciences
                Data Visualization
                Research and Analysis Methods
                Chemical Characterization
                Mass Analysis
                Density Analysis
                Biology and Life Sciences
                Physiology
                Biological Locomotion
                Climbing
                Medicine and Health Sciences
                Physiology
                Biological Locomotion
                Climbing
                People and Places
                Geographical Locations
                Asia
                Korea
                People and places
                Geographical locations
                Asia
                South Korea
                Biology and Life Sciences
                Developmental Biology
                Organism Development
                Aging
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Aging
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Aging
                Custom metadata
                Data were obtained from the third party site www.data.go.kr. All traffic accident data files are available from https://www.data.go.kr/dataset/15003493/fileData.do. The authors confirm that they did not have any special access privileges to these data.

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