Integrating Spatial Analysis for Urban Road Safety

Urbanization in Pakistan has surged in recent years, with the urban population rising from 37.2% in 2015 to 41.5% by 2024 (World Bank, 2024). This rapid demographic shift has strained the infrastructure of major cities, particularly in terms of traffic management and road safety. Cities like Karachi, Lahore, Islamabad, Peshawar, and Quetta face mounting challenges, including traffic congestion, poor road conditions, lack of pedestrian infrastructure, and inadequate enforcement of traffic laws. According to the Pakistan Bureau of Statistics (2023), more than 15,000 people lose their lives annually in road accidents, while another 30,000 suffer serious injuries. These accidents not only cause human suffering but also impose an economic burden of approximately 3% of the national GDP due to medical costs, lost productivity, and property damage (Asian Development Bank, 2023).

While road safety has become a pressing issue in Pakistan’s urban areas, academic and policy discourse remains limited in its analytical depth. Most existing studies rely on descriptive or temporal data, missing the critical spatial dimensions that could uncover localized risk patterns and high-incidence zones. This study seeks to address this analytical gap by utilizing advanced spatial analysis techniques including Geographic Information Systems (GIS), hotspot identification, and spatial regression modeling to systematically map road accident distribution across major Pakistani cities.

By pinpointing high-risk zones and understanding the geographical correlates of accidents, this article aims to offer actionable insights for urban planners, transportation authorities, and law enforcement agencies. Spatially informed road safety interventions such as traffic calming measures, redesign of accident-prone intersections, and targeted enforcement can substantially reduce fatalities and improve urban mobility. The study ultimately supports a data-driven approach to urban development, fostering safer, more resilient cities amid Pakistan’s rapid urban expansion.

Advancing Spatial Understanding of Road Accidents in Pakistan’s Urban Centers

Spatial analysis has become a pivotal tool globally for understanding the dynamics of road traffic accidents. In developed countries such as those in Europe and North America, Geographic Information Systems (GIS) and advanced clustering methods like Kernel Density Estimation (KDE) and Getis-Ord Gi* are widely employed to identify accident-prone zones and guide urban safety interventions (Li et al., 2022). In South Asia, nations like India and Bangladesh have used spatial autocorrelation techniques, including Moran’s I, to explore accident patterns near highways, intersections, and high-density urban corridors (Das & Ahmed, 2021). These approaches have enabled policymakers to target infrastructure improvements and enforcement in high-risk areas.

In contrast, Pakistan's research on road safety has been limited, often relying on temporal and descriptive statistical methods rather than spatially grounded analysis. Some recent studies have begun to fill this gap. For example, Ahmed and Abbas (2018) mapped accident hotspots in Lahore, while Khan and Fatima (2021) explored high-risk corridors in Karachi. However, such studies are typically restricted to single cities and lack the integration of spatial econometrics, multi-city comparisons, and longitudinal data analysis.

The pressing need for more advanced spatial research in Pakistan is underscored by multiple systemic issues contributing to road accidents. These include deteriorating road infrastructure, with nearly 40% of national highways lacking proper signage (NHA, 2023), prevalent risky driver behaviors such as over-speeding and lane violations, and a lack of robust enforcement. 30% of traffic laws are consistently applied (Punjab Police, 2024). Additionally, pedestrian infrastructure remains severely inadequate, with less than 20% of urban roads equipped with functional footpaths (Karachi Urban Lab, 2023).

This study builds on and extends prior research by applying sophisticated spatial analytical tools across five major Pakistani cities. It uses geocoded accident data from 2015 to 2024 to identify spatial clusters and statistically significant risk factors, aiming to inform smarter urban design and policy interventions tailored to Pakistan’s evolving urban landscapes.

Geospatial Analysis Framework for Urban Road Safety in Pakistan

A recent study focused on understanding the spatial patterns and determinants of road traffic accidents across five major Pakistani cities i.e. Karachi, Lahore, Islamabad, Peshawar, and Quetta. These urban centers were chosen based on their high population density, rapid urban expansion, and the availability of comprehensive traffic data. Karachi, for instance, is characterized by a complex and often informal road network, with 30% of its traffic flow estimated to be unregulated (Sindh Transport Authority, 2024). Lahore presents a hybrid infrastructure of historical roads and modern highways, recording the highest motorcycle accident rate in Pakistan. Islamabad, despite being a planned city, struggles with an 8% annual vehicle growth rate, which overwhelms its existing road infrastructure (ICT Administration, 2024). Meanwhile, Peshawar and Quetta, experiencing swift urbanization, lack essential road safety infrastructure and enforcement mechanisms (KP & Balochistan Transport Departments, 2023).

The research uses a combination of primary and secondary data sources, including police accident reports, Rescue 1122 records, hospital trauma registries, road network data from OpenStreetMap, and census-based population and infrastructure statistics. Key variables collected for each accident include GPS location, severity classification, vehicle types involved, and contextual factors such as weather, time, and road conditions.

Three spatial analysis techniques were employed to extract meaningful insights. Moran’s I measured overall spatial autocorrelation, confirming statistically significant clustering of accidents (p < 0.01). Hotspot analyses using Getis-Ord Gi* and Kernel Density Estimation helped identify high-risk corridors, while spatial regression modeling assessed how road type, traffic volume, and urban infrastructure impacted accident rates. Results showed that Karachi reported the highest annual accident figures (approximately 9,200), with critical clusters around Shahrah-e-Faisal and Korangi industrial zone. Lahore followed with 7,500 incidents annually, notably along Ferozepur Road and Ring Road junctions. Islamabad’s hotspots were concentrated in the Blue Area and Faizabad, while Peshawar and Quetta reported lower but rising trends.

Notable risk factors include inadequate road design (60% of hotspots lacked proper signage), traffic violations such as speeding (35%) and illegal U-turns (20%), and pedestrian vulnerability, where only 15% of crossings were signalized. These findings underscore the urgency of data-driven policy interventions. Recommendations include upgrading infrastructure with smart traffic signals and pedestrian bridges, enhancing enforcement via e-challan systems and increased patrolling, and implementing public safety campaigns. Additionally, real-time GIS-based monitoring systems should be developed to proactively identify and manage future risk zones, fostering safer urban mobility across Pakistan.

Conclusion

This study underscores the urgent need to integrate spatial analysis into urban road safety planning in Pakistan. As urbanization intensifies, cities like Karachi, Lahore, Islamabad, Peshawar, and Quetta are experiencing rising traffic volumes, deteriorating infrastructure, and inadequate enforcement—factors that contribute to thousands of fatalities and injuries annually. By leveraging Geographic Information Systems (GIS), hotspot analysis, and spatial regression techniques, this research identifies critical accident-prone zones and the underlying risk factors, such as poor road design, pedestrian unfriendliness, and reckless driving behaviors.

Findings confirm statistically significant clustering of accidents, with urban centers like Karachi and Lahore showing pronounced hotspots along major commercial and industrial corridors. The study offers actionable insights for policymakers, emphasizing infrastructure upgrades, smart enforcement tools like e-challans, and public awareness campaigns. Importantly, it advocates for real-time, spatially informed monitoring systems that can proactively reduce accident rates rather than relying solely on reactive measures.

This spatially grounded approach provides a roadmap for urban planners, traffic authorities, and local governments to adopt data-driven solutions tailored to each city’s unique risk profile. As Pakistan's cities continue to grow, embracing such evidence-based strategies is essential to ensure safer, more resilient, and more sustainable urban mobility systems for the future.

References: ADB; Khan & Fatima; World Bank; Punjab Emergency Service; Pakistan Bureau of Statistics; Asian Development Ban; Li et al; Das & Ahmed; Ahmed & Abbas; NHA; Karachi Urban Lab; Sindh Transport Authority; ICT Administration KP & Balochistan Transport Departments

Please note that the views expressed in this article are of the author and do not necessarily reflect the views or policies of any organization.

The writer is affiliated with the Department of Statistics, Sindh Agriculture University, Tandojam, Sindh, Pakistan and can be reached at aftabkarem@gmail.com

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