Browse > Article
http://dx.doi.org/10.7319/kogsis.2014.22.3.099

Pattern Analysis for Urban Spatial Distribution of Traffic Accidents in Jinju  

Sung, Byeong Jun (BK21+, Urban engineering, Gyeongsang National University)
Yoo, Hwan Hee (BK21+, ERI, Urban engineering, Gyeongsang National University)
Publication Information
Journal of Korean Society for Geospatial Information Science / v.22, no.3, 2014 , pp. 99-105 More about this Journal
Abstract
Since traffic accidents account for the highest proportion of the artificial disasters which occur in urban areas along with fire, more scientific an analysis on the causes of traffic accidents and various prevention measures against traffic accidents are needed. In this study, the research selected Jinju-si, which belongs to local small and medium-sized cities as a research target to analyze the characteristics of temporal and spacial distribution of traffic accidents by associating the data of traffic accidents, occurred in 2013 with the causes of traffic accidents and location information that includes occurrence time and seasonal features. It subsequently examines the spatial correlation between traffic accidents and the characteristics of urban space development according to the plans of land using. As a result, the characteristics of accident distribution according to the types of accidents reveal that side right-angle collisions (car versus car) and pedestrian-crossing accident (car versus man) showed the highest clustering in the density analysis and average nearest neighbor analysis. In particular, traffic accidents occurred the most on roads which connect urban central commercial areas, high-density residential areas, and industrial areas. In addition, human damage in damage conditions, clear day in weather condition, dry condition in the road condition, and three-way intersection in the road way showed the highest clustering.
Keywords
Traffic Accidents; Density Analysis; Nearest Neighbor Analysis; Plans of Land Using; Spatial Correlation;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Chen, M. S., Han, J. and Yu, P. S., 1996, Data mining: overview from database perspective, IEEE Transactions Knowledge and Data Engineering, pp. 1-40.
2 Jeon, M. H., 2012, Traffic safety facilities to prevent car accidents in school zones, Master's Thesis, Hongik University Graduate School.
3 Jo, S. I., 2009, Analyses on the relations between school zone with gis and the incidence of car accidents, Master's Thesis, Korea National University of Education Graduate School of Education.
4 Jo, S. M., 2009, Study on environmental improvements and examinations of driver's consciousness in child safety area(school zone) for the prevention of traffic accidents, Master's Thesis, Ajou University ITS Graduate School.
5 Kim, T. Y., 2007, Analysis of loop and direct-ramp driving condition and traffic accidents in the case of Trumpet Interchange, Korean Society of Transportation, Vol. 2007, No. 3, pp. 404-411.
6 Lee, C. H., 2005, Analysis of the factors having an influence on the crossroad traffic accident and of their characteristics, Master's Thesis, Kyungil University Graduate School.
7 Park, G. Y., 2006, Evaluation of accident reduction effect of road safety features and development of estimation model for accident reduction factors, Doctorate Thesis, University of Seoul Graduate School.
8 Lee, G. H., 2003, A study of spatial patterns of traffic accident using gis and spatial data mining method: a case study of kangnam-gu, seoul, The Korean Geographical Society, Vol. 39, No. 3, pp. 457-472.
9 Lee, H.Y. and Sim, J. H.,Geographical information systems, Bobmunsa, pp. 373-383.
10 O'Sullivan, D., and Unwin, D. J., 2010, Geographic information analysis -2nd ed., John Wiley & Sons, Inc., Hoboken, New Jersey, USA, pp. 121-155.
11 Park, J. Y., 2011, Development of macroscopic traffic accident analysis model by regional characteristics, Master's Thesis, University of Seoul Graduate School.
12 Sung, B. J.. 2014. Spatial cluster analysis of traffic accidents in jinju City, Proceeding of Korean Society for Geospatial Information System, pp. 169-172.