User menu

Intra-urban location and clustering of road accidents using GIS: a Belgian example

Bibliographic reference Steenberghen, T ; Dufays, T ; Thomas, Isabelle ; Flahaut, B. Intra-urban location and clustering of road accidents using GIS: a Belgian example. In: International Journal of Geographical Information Science, Vol. 18, no. 2, p. 169-181 (2004)
Permanent URL
  1. Anselin L 1988Spatial Econometrics: Methods and Models(Dordrecht: Kluwer)
  2. Anselin L 1995 Local indicators of spatial association—LISAGeographical Analysis,27(2), 93–115
  3. Bailey T. C Gatrell A. C 1996Interactive Spatial Data Analysis(Harlow, UK: Longman)
  4. Banos A 1999 Quelle implication de l'utilisateur dans une stratégie de Data Mining spatial?Revue internationale de géomatique,9(4/1999), 441–456
  5. Black W. R Thomas I 1998 Accidents on Belgium's motorways: a network autocorrelation analysisJournal of Transport Geography,6(1), 23–31
  6. Cliff A. D Ord J. K 1973Spatial Autocorrelation(London: Pion)
  7. Cliff A. D Ord J. K 1981Spatial Processes. Models and Applications(London: Pion)
  8. Flahaut Benoı̂t, Mouchart Michel, Martin Ernesto San, Thomas Isabelle, The local spatial autocorrelation and the kernel method for identifying black zones, 10.1016/s0001-4575(02)00107-0
  9. Flahaut Benoît, Thomas Isabelle, Identifier les zones noires d'un réseau routier par l'autocorrélation spatiale locale Analyses de sensibilité et aspects opérationnels, 10.3166/rig.12.245-261
  10. Getis A Ord J. K 1992 The analysis of spatial association by use of distance statisticsGeographical Analysis,24(3), 189–206
  11. Griffith D. A 1987Spatial Autocorrelation: A Primer(Washington, DC: Association of American Geographers, Resource Publications in Geography)
  12. Haining R 1990Spatial Data Analysis in the Social and Environmental Sciences(Cambridge: Cambridge University Press)
  13. Hauer E 1996 Identification of sites with promise InTransportation Research Record 1542, 75thAnnual Meeting, Washington, DC, pp. 54–60
  14. Hope A. C. A, Journal of the Royal Statistical Society, 30, 582 (1968)
  15. Huguenin-Richard F 1999 Identifier les sites routiers dangereux; application de methodes d'analyse utilisant la localisation géographique des accidentsRevue internationale de géomatique,9(4), 471–487
  16. Joly M-F Bourbeau R Bergeron J Messier S 1992 Analytical Approach to the Identification of Hazardous Road Locations: A Review of the Literature Centre de recherche sur les transports, Université de Montréal, CRT publication No. 815
  17. Marriott F. H. C., Barnard's Monte Carlo Tests: How Many Simulations?, 10.2307/2346816
  18. Moran P, Journal of the Royal Statistical Society, 10, 243 (1948)
  19. Nguyen T. N 1991 Identification of Accident Blackspot Locations, an Overview VIC Roads/Safety Division, Research and Development Department, Australia. VIC Discussion Paper (DP/91/4)
  20. Openshaw Stan, Developing Automated and Smart Spatial Pattern Exploration Tools for Geographical Information Systems Applications, 10.2307/2348611
  21. Openshaw S Turton I 2001 Geographical analysis machine on the Internet http://www/
  22. Ord J. K., Getis Arthur, Local Spatial Autocorrelation Statistics: Distributional Issues and an Application, 10.1111/j.1538-4632.1995.tb00912.x
  23. Ormsby T Napoleon E Breslin P Frunzi N 1998Getting to Know ArcviewGIS 3.x: The Geographic Information System (GIS) for Everyone(Redlands, CA: ESRI Press)
  25. Silcock D. T Smyth A. W 1985 Methods of Identifying Accidents Blackspots Transport Operations Research Group, Department of Civil Engineering, University of Newcastle upon Tyne. TORG Research Report 1985
  26. Silverman B. W 1986Density Estimation for Statistics and Data Analysis(New York: Chapman & Hall)
  27. Tiefelsdorf M 2000Modelling Spatial Processes. Lecture Notes in Earth Sciences 87(Berlin: Springer)
  28. Vandersmissen M. H, Recherche Transports Sécurité, 51, 49 (1996)