Space time dynamics of road crashes occurrence in Punjab, Pakistan: A GIS Perspective

Space Time Dynamics of RTCs in Punjab, Pakistan

  • Khalid Mahmood Department of Space Science, University of the Punjab, Lahore-54590, Pakistan
  • Rida Batool Remote Sensing, GIS and Climate Research Lab (National Center of GIS and Space Applications), Center for Remote Sensing, University of the Punjab, Lahore-54590, Pakistan
  • Roqya Bano Javed Punjab Emergency Services, Rescue 1122, Lahore, Pakistan
  • Fiza Faizi Remote Sensing, GIS and Climate Research Lab (National Center of GIS and Space Applications), Center for Remote Sensing, University of the Punjab, Lahore-54590, Pakistan
Keywords: road traffic crashes, spatio-temporal analysis, emergency management, geospatial technologies, geographic information system (GIS)

Abstract

This study proposes a comprehensive Geographic Information System (GIS) based time series analysis of varying trends of Road Traffic Crashes (RTCs) in different regions of province Punjab, Pakistan. GIS provides geographical framework to analyze spatial characteristics of a particular event for accurate road safety risk assessment. In order to evaluate potentially emerging accident ratios, monthly data based on RTCs from 2015 to 2018 collected from all the units of study area is initially geographically displayed using GIS. The results and analysis has been based on 3125094 emergency events occurred in Punjab, providing a strong base to the conclusive spatio-temporal patterns. The peak RTCs regions of Lahore, Faisalabad, Gujranwala and Multan have been studied for 227111, 102276, 64036 and 70194 events  occurred in the four year span, whereas the rate of annual increase in RTCs in these cities has been measured to be 11153, 3229, 1730 and 4000 respectively. A comparative analysis of time rate of change of RTCs not only highlights varying trends along mutually bounded regions but also reveals prominence of seasonal and local factors behind increasing and decreasing ratios of road accidents. However, despite limited local information regarding road crash events, conclusions suggest that GIS based temporal analytical practices for precise risk assessment provide a cost effective decision support system to local administration and policy makers.

 

Published
2022-10-19