Identification of Accident Hot Spots at Different Roads of Midnapore Municipality Area: A Geoinformatic Approach

Abstract

Road traffic injuries (RTIs) are a huge public health and development problem, killing almost 1.2 million people a year and injuring or disabling almost 20 to 50 million or more. Both WHO and World Bank data show that without appropriate action these injuries will rise dramatically by the year 2020, particularly in rapidly-motorizing countries. The study identifies the volatile traffic areas where road accidents are almost regular events and assess the temporal variation of these traffic accidents and injuries in Midnapore municipal area through Spatial Information Technology (SIT). By applying Kernel-density method in identifying accident-prone locations in Midnapore municipal area, three accident-prone zones are observed. This result shows highest concentration of a particular type of accidents and is useful for looking at patterns rather than at locations of individual features. This work gives an insight into the present scenario of the traffic conditions, road width, land use/land cover of the area and shows the most accident-prone roads. In future, accidents can be reduced by eliminating unsafe conditions and reducing unsafe acts. This work will give an insight into the traffic scenario and will give planners and traffic authorities some breathing space when considering long-term objectives and likely solutions of the problem.

Keywords: Kernel density, spatial information technology (SIT), temporal variation, pattern analysis