PL EN


Preferences help
enabled [disable] Abstract
Number of results
2017 | 10 | 1-9
Article title

Influencing Spatial and Temporal Patterns of Road Accidents: A Study on Nuwara – Eliya District

Content
Title variants
Languages of publication
EN
Abstracts
EN
In the global context, about 1.25 million people die each year as a result of road traffic crashes. Moreover, road traffic injuries are the leading cause of death among young people, aged 15–29 years. Furthermore, 90% of the world's road fatalities occur in low- and middle-income countries (WHO, 2017). In Sri Lanka, the accident rate is increasing rapidly. According to the transport and civil aviation report, 2801 deaths, 2590 fatal accidents, 13,095 minor accidents, and 7719 critical accidents occurred in Sri Lanka in 2015. The trend of the accidents has been increasing due to many factors. Physical features of the roads and roadsides, behaviour of drivers and pedestrians are the main influence on the occurrence of accidents. Central province has many accidents-prone areas due to its spatial and temporal patterns. Landform and climatic factors such as fog, snow and rainfall trigger accident potentials. Therefore, this study, “Spatial and temporal patterns of road accidents and their challenges: a study on Nuwara-Eliya District” investigates reasons for the enhanced rate of traffic mishaps. This is the first such study of this phenomenon. Herein, we used primary and secondary data. The results indicate that physical features are mainly to blame.
Keywords
Year
Volume
10
Pages
1-9
Physical description
Contributors
  • Department of Geography, South Eastern University of Sri Lanka, Oluvil, Sri Lanka, mimkaleel@yahoo.com
  • Department of Geography, South Eastern University of Sri Lanka, Oluvil, Sri Lanka
References
  • [1] M. I. M. Kaleel, Pipe-borne water consumption and its wastage: A study based on Panandura Urban Area in Sri Lanka. World Scientific News 66 (2017) 250-262
  • [2] Ned Levine, Karl E. Kim, Lawrence H. Nitz. Spatial analysis of Honolulu motor vehicle crashes: I. Spatial patterns. Accident Analysis & Prevention Volume 27, Issue 5, October 1995, Pages 663-674
  • [3] Anselin, L. (1995). Local Indicators of Spatial Association—LISA. Geographical Analysis 27 (2), 93–115.
  • [4] Besag, J., and J. Newell. (1991). The Detection of Clusters in Rare Diseases. Journal of the Royal Statistical Society Series A 154 (1), 143–55.
  • [5] Black, W. R. (1991). Highway Accidents: A Spatial and Temporal Analysis. Transportation Research Record 1318, 75–82.
  • [6] Black, W. R. (1992). Network Autocorrelation in Transport Network and Flow Systems. Geographical Analysis 24, 207–22.
  • [7] Cirillo, J. A. (1968). Interstate System Accident Research Study II, Interim Report II. Public Roads 35 (3), 71–75.
  • [8] Clark, P. J., and F. C. Evans. (1954). Distance to Nearest Neighbor as a Measure of Spatial Relationships in Population. Ecology 35, 445–53.
  • [9] Cressie, N., and B. Collins. (2001). Patterns in Spatial Point Locations: Local Indicators of Spatial Association in a Minefield with Clutter. Naval Research Logistics 48, 333–47.
  • [10] Flahaut, B., M. Mouchart, E. S. Martin, and I. Thomas. (2003). The Local Spatial Autocorrelation and the Kernel Method for Identifying Black Zones: A Comparative Approach. Accident Analysis and Prevention 35, 991–1004.
Document Type
article
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.psjd-5d9bcc10-09e9-4356-9716-5a394215d341
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.