Comparison of planar and network K-functions in traffic accident analysis

Journal of Transport Geography

Volumn 12, Issue 2, 2004, Pages 149-158

  Yamada, Ikuho ^a   Thill, Jean Claude ^a  

^a UNIVERSITY AT BUFFALO   (United States)

Author keywords

K function analysis; Monte Carlo simulation; Networks; Point pattern analysis; Traffic accidents

Indexed keywords

TRANSPORTATION SAFETY;

BUBALUS;

EID: 1942520407     PISSN: 09666923     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jtrangeo.2003.10.006     Document Type: Article

References (27)

1. Bailey T.C. Gatrell A.C. Interactive Spatial Data Analysis 1995 Longman Harlow
2. Bartlett M.S. The spectral analysis of two-dimensional point process Biometrika 51 3 - 4 1964 299-311
3. Barot S. Gignoux J. Menaut J.-C. Demography of a savanna palm tree: predictions from comprehensive spatial pattern analysis Ecology 80 6 1999 1987-2005
4. Black W.R. Highway accidents: a spatial and temporal analysis Transportation Research Record 1318 1991 75-82
5. Black W.R. Network autocorrelation in transport network and flow systems Geographical Analysis 24 1992 207-222
6. Black W.R. Thomas I. Accidents in Belgium's motorways: a network autocorrelation analysis Journal of Transport Geography 6 1 1998 23-31
7. Cressie N. Statistics for Spatial Data 1993 John Wiley - Sons New York
8. Diggle P.J. Spatial Analysis of Spatial Point Patterns 1983 Academic Press New York
9. Fotheringham A. Brunsdon C. Charlton M. Quantitative Geography: Perspectives on Spatial Data Analysis 2000 Sage Publication London
10. Getis A. Second-order analysis of point patterns: the case of Chicago as a multi-center urban region The Professional Geographer 35 1 1983 73-80
11. He F. Duncan R.P. Density-dependent effects on tree survival in an old-growth Douglas Fir forest The Journal of Ecology 88 4 2000 676-688
12. Jones A.P. Langford I.H. Bentham G. The application of K-function analysis to the geographical distribution of road traffic accident outcomes in Norfolk, England Social Science and Medicine 42 6 1996 879-885
13. Kwan M-P. Space-time and integral measures of individual accessibility: a comparative analysis using a point-based framework Geographical Analysis 30 3 1998 191-216
14. Levine N. Kim K.E. Nitz L.H. Spatial analysis of Honolulu motor vehicle crashes: I. Spatial Patterns Accident Analysis and Prevention 27 5 1995 663-674
15. Levine N. Kim K.E. Nitz L.H. Spatial analysis of Honolulu motor vehicle crashes: II. Zonal Generators Accident Analysis and Prevention 27 5 1995 675-685
16. McGuigan D.R.D. The use of relationships between road accidents and traffic flow in 'Black-spot' identification Traffic Engineering and Control 22 1981 448-453
17. Miller H.J. Market area delineation within networks using geographic information systems Geographical Systems 1 2 1994 157-173
18. Miller H.J. Measuring space-time accessibility benefits within transportation networks Geographical Analysis 31 2 1999 187-212
19. Miller H.J. Potential contribution of spatial analysis to geographic information systems for transportation (GIS-T) Geographical Analysis 31 4 1999 373-399
20. Okabe A. Yomono H. Kitamura M. Statistical analysis of the distribution of points on a network Geographical Analysis 27 2 1995 152-175
21. Okabe A. Kitamura M. A computational method for market area analysis on a network Geographical Analysis 28 4 1996 330-349
22. Okabe A. Okunuki K. A computational method for estimating the demand of retail stores on a street network using GIS Transactions in GIS 5 3 2001 209-220
23. Okabe A. Yamada I. The K-function method on a network and its computational implementation Geographical Analysis 33 3 2001 271-290
24. Rechel, J.L., Nicholson, M.C., 1994. Spatial Pattern Analysis of Mule Deer Locations in the San Bernardino Mountains, California. GIS/LIS '94, pp. 643-657
25. Ripley B.D. The second-order analysis of stationary point process Journal of Applied Probability 13 1976 255-266
26. Ripley B.D. Spatial Statistics 1981 John Wiley - Sons Chichester
27. Yamada I. Rogerson P.A. An empirical comparison of edge effect correction methods applied to K-function analysis Geographical Analysis 35 2 2003 97-109