1 |
Park, J. and Han, M. (2014), A study on the implementation of walking environment projects by analyzing characteristics of pedestrian accidents by local government types, Journal of Korean Society of Transportation, Vol. 32, No. 6, pp. 615-627. (in Korean with English abstract)
DOI
|
2 |
Plug, C., Xia, J., and Caulfield, C. (2011), Spatial and temporal visualisation techniques for crash analysis, Accident Analysis and Prevention, Vol. 43, No. 6, pp. 1937-1946.
DOI
|
3 |
Pulugurtha, S.S., Krishnakumar, V.K., and Nambisan, S.S. (2007), New methods to identify and rank high pedestrian crash zones, Accident Analysis and Prevention, Vol. 39, No. 4, pp. 800-811.
DOI
|
4 |
Anderson, T.K. (2009), Kernel density estimation and k-means clustering to profile road accident hotspots, Accident Analysis and Prevention, Vol. 41, No. 3, pp. 359-364.
DOI
|
5 |
Tobler, W.R. (1970), A computer movie simulating urban growth in the Detroit region, Economic Geography, Vol. 46, pp. 234-240.
DOI
|
6 |
Rankavat, S. and Tiwari, G. (2013), Pedestrian accident analysis in Delhi using GIS, Journal of the Eastern Asia Society for Transportation Studies, Vol. 10, pp. 1446-1457.
|
7 |
Schabenberger, O. and Gotway, C.A. (2005), Statistical Methods for Spatial Data Analysis, Chapman & Hall/CRC, Boca Raton, Florida.
|
8 |
Silverman, B.W. (1986), Probability Density Estimation for Statistics and Data Analysis, Chapman and Hall, New York, N.Y.
|
9 |
Truong, L.T. and Somenahalli, S.V.C. (2011), Using GIS to identify pedestrian-vehicle crash hot spots and unsafe bus stops, Journal of Public Transportation, Vol. 14, No. 1, pp. 99-114.
DOI
|
10 |
Vemulapalli, S.S. (2015), GIS-Based Spatial and Temporal Analysis of Aging-Involved Crashes in Florida, Master's thesis, Florida State University, Florida, USA, 126p.
|
11 |
Xie, Z. and Yan, J. (2008), Kernel density estimation of traffic accidents in a network space, Computers, Environment, and Urban Systems, Vol. 32, No. 5, pp. 396-406.
DOI
|
12 |
Jang, M., Jang, J., Joo, S., and So, K. (2012), Evaluations of pedestrian environment improvement plan and its performance, Transportation Technology and Policy, Vol. 9, No. 2, pp. 77-85. (in Korean)
|
13 |
Jo, J., Park, W., and Kim, M. (2014), Development and application of traffic safety forecast index based on weather informations, Transportation Technology and Policy, Vol 11, No. 2, pp. 62-71. (in Korean)
|
14 |
Khan, G., Qin, X., and Noyce, D. (2008), Spatial analysis of weather crash patterns, Journal of Transportation Engineering, Vol. 134, No. 5, pp. 191-202.
DOI
|
15 |
Flahaut, B., Mouchart, M., Martin, E.S., and Thomas, I. (2003), The local spatial autocorrelation and the kernel method for identifying black zones, Accident Analysis and Prevention, Vol. 35, No. 6, pp. 991-1004.
DOI
|
16 |
Bailey, T.C. and Gatrell, A.C. (1995), Interactive Spatial Data Analysis, Longman, Essex, UK.
|
17 |
Jang, K., Park. S.H., Kang, S., Song, K.H., Kang, S., and Chung, S. (2013), Evaluation of pedestrian safety: pedestrian crash hot spots and risk factors for injury severity, Transportation Research Record: Journal of the Transportation Research Board, Vol. 2393, pp. 104-116.
DOI
|
18 |
Blazquez, C.A. and Celis, M.S. (2013), A spatial and temporal analysis of child pedestrian crashes in Santiago, Chile, Accident Analysis and Prevention, Vol. 50, pp. 304-311.
DOI
|
19 |
Kuo, P., Zeng, X., and Lord, D. (2011), Guidelines for choosing hot-spot analysis tools based on data characteristics, network restrictions, and time distributions, Proceedings of the 91st Annual Meeting of the Transportation Research Board, Transportation Research Board, 22-26 January, Washington, D.C., USA. pp. 1-21.
|
20 |
Kingham, S., Sabel, C.E., and Bartie, P. (2011), The impact of the school run on road traffic accidents: a spatio-temporal analysis, Journal of Transport Geography, Vol. 19, No. 4, pp. 705-711.
DOI
|
21 |
Loo, B.P.Y., Yao, S., and Wu, J. (2011), Spatial point analysis of road crashes in shanghai: a GIS-based network kernel density method, Proceedings of 19th International Conference on Geoinformatics, IEEE, 24-26 June, Shanghai, China, pp. 1-6.
|
22 |
Manepalli, U.R.R., Bham, H.G., and Kandada, S. (2011), Evaluation of hotspots identification using kernel density estimation (K) and Getis-ord (Gi*) on I-630, Proceedings of the 3rd International Conference on Road Safety and Simulation, Transportation Research Board, 14-16 September, Indianapolis, USA, pp.1-17.
|
23 |
Prasannakumar, V., Vijith, H., Charutha, R., and Geetha, N. (2011), Spatio-temporal clustering of road accidents: GIS based analysis and assessment, Procedia Social and Behavioral Sciences, Vol. 21, pp. 317-325.
DOI
|
24 |
O'Sullivan, D. and Unwin, D.J. (2002), Geographic Information Analysis, John Wiley & Sons Inc., Hoboken, N.J.
|