Journal of the Indian Society of Remote Sensing

, Volume 47, Issue 1, pp 101–111 | Cite as

Application of a Geographic Information System to Analyze Traffic Accidents Using Nantou County, Taiwan, as an Example

  • Jau-Ming Su
  • Yu-Ming WangEmail author
  • Chih-hung Chang
  • Pei-Ju Wu
Research Article


A geographic information system (GIS) is a commonly used method for analyzing traffic accidents. Through a GIS, data regarding traffic accidents can be presented visually, and traffic accident locations can be analyzed. By identifying locations where traffic accidents frequently occur and highway sections with high accident rates, traffic authorities can adopt preventive measures and enforce traffic regulations to reduce the frequency of traffic accidents, deaths, injuries, and financial losses. The present study analyzed tourist traffic accidents in Nantou County, one of the most popular tourist areas in Taiwan for domestic and international travelers, and tabulated statistical data that were subsequently input into a GIS database to determine dangerous locations and areas where traffic accidents are prone to occur. First, administrative regions in Nantou County were identified and kernel density estimation and repeatability analysis were performed to determine locations with high accident rates. The results showed that in Nantou County, traffic accidents often occur between 12:00 and 18:00 at intersections and on sloped roads and windy roads. The most dangerous locations were Provincial Highway 21 (areas around Sun Moon Lake) and Provincial Highway 14A (areas with access to Qingjing and Hehuanshan). The results of this study could serve as a reference for traffic authorities to develop measures for preventing and regulating traffic accidents.


Traffic accident Geographic information system Dangerous location Kernel density estimation 


  1. Ansari, D. G. A., & Al-shabi, D. M. (2012). Modeling of traffic accident reporting system through UML using GIS. International Journal of Advanced Computer Science and Applications (IJACSA).
  2. Bailey, T. C., & Gatrell, A. C. (1995). Interactive spatial data analysis (1st ed.). Harlow Essex, New York, NY: Routledge.Google Scholar
  3. Benedek, J., Ciobanu, S. M., & Man, T. C. (2016). Hotspots and social background of urban traffic crashes: A case study in Cluj-Napoca (Romania). Accident Analysis and Prevention, 87, 117–126. Scholar
  4. Cai, M., Zou, J., Xie, J., & Ma, X. (2015). Road traffic noise mapping in Guangzhou using GIS and GPS. Applied Acoustics, 87, 94–102. Scholar
  5. Erdogan, S., Yilmaz, I., Baybura, T., & Gullu, M. (2008). Geographical information systems aided traffic accident analysis system case study: City of Afyonkarahisar. Accident Analysis and Prevention, 40(1), 174–181. Scholar
  6. Gaikwad, D. B., Wanjari, Y. W., & Kale, K. V. (2014). Accident analysis system by integration of spatial data mining with GIS Web Services. International Journal of Computer Applications, 103(10), 15–22.CrossRefGoogle Scholar
  7. Hashimoto, S., Yoshiki, S., Saeki, R., Mimura, Y., Ando, R., & Nanba, S. (2016). Development and application of traffic accident density estimation models using kernel density estimation. Journal of Traffic and Transportation Engineering (English Edition), 3(3), 262–270. Scholar
  8. Institute of Transportation. (2003). Technical reference manual for hazardous location improvement. Ministry of Transportation and Communications.Google Scholar
  9. Kaygisiz, Ö., Düzgün, Ş., Yildiz, A., & Senbil, M. (2015). Spatio-temporal accident analysis for accident prevention in relation to behavioral factors in driving: The case of South Anatolian Motorway. Transportation Research Part F: Traffic Psychology and Behaviour, 33, 128–140. Scholar
  10. Khan, M. A., & Kathairi, A. S. A. (2004). A GIS based traffic accident data collection, referencing and analysis framework for Abu Dhabi. Presented at the Codatu XI: Towards more attractive urban transportation, Bucharest, Romania.Google Scholar
  11. Kumaresan, V., Vasudevan, V., & Nambisan, S. S. (2009). Development of a GIS-based traffic safety analysis system. Presented at the 2009 annual ESRI international user conference, San Diego, California.Google Scholar
  12. Loo, B. P. Y. (2006). Validating crash locations for quantitative spatial analysis: A GIS-based approach. Accident Analysis and Prevention, 38(5), 879–886. Scholar
  13. Reshma, E., & Sharif, S. U. (2012). Prioritization of accident black spots using GIS. International Journal of Emerging Technology and Advanced Engineering, 2(9), 117–122.Google Scholar
  14. Rodrigues, D. S., Ribeiro, P. J. G., & da Silva Nogueira, I. C. (2015). Safety classification using GIS in decision-making process to define priority road interventions. Journal of Transport Geography, 43, 101–110. Scholar
  15. Sandhu, H. A. S., Singh, G., Sisodia, M. S., & Chauhan, R. (2016). Identification of black spots on highway with kernel density estimation method. Journal of the Indian Society of Remote Sensing, 44(3), 457–464. Scholar
  16. Steenberghen, T., Dufays, T., Thomas, I., & Flahaut, B. (2004). Intra-urban location and clustering of road accidents using GIS: A Belgian example. International Journal of Geographical Information Science, 18(2), 169–181. Scholar
  17. Varela, A. M., Muñoz-Tuñón, C., García-Lorenzo, B., & Fuensalida, J. J. (2006). Tropospheric wind regimes and site topographical effects: Importance for site characterization (Vol. 6267, p. 62671X). Presented at the Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series.
  18. Wang, M. H., Kuo, C. C., & Chen, C. C. (2010). Applying a geographic information system to correlation analysis of traffic accidents, traffic law enforcement, and road characteristics (pp. 189–198). Presented at the 2010 Traffic Safety and Law Enforcement Conference, Taoyuan.Google Scholar

Copyright information

© Indian Society of Remote Sensing 2018

Authors and Affiliations

  1. 1.Department of Transportation and LogisticsFeng Chia UniversityTaichungTaiwan, ROC
  2. 2.Ph.D. Program of Technology ManagementChung Hua UniversityHsin ChuTaiwan, ROC

Personalised recommendations