Modeling geospatial determinants of pedestrian fatalities on high-speed rural roads using satellite imagery: A statewide analysis from Haryana, India.

Abstract

Objective: Pedestrian fatalities on high-speed rural roads in low- and middle-income countries remain an underexplored but critical road safety issue. This study investigates pedestrian safety on high-speed rural roads in Haryana, India, spanning 5,069 km.

Methods: A geospatial methodology was developed to assess changes in land use and population distribution within a 500 m buffer from 2017 to 2022 using satellite imagery. Sentinel-2 imagery and population density data helped estimate growth in built-up areas and demographic shifts. Fatality rates per 100 km and 10,000 population were calculated to identify high-risk corridors.

Results: Analysis of 4,020 pedestrian fatalities showed peak occurrences in the evenings (7-9 PM), with the highest share on Sundays and in winter. Generalized Poisson and Negative Binomial (NB) regression models examined the impact of road, landuse, and demographic variables, with the NB model showing a better fit. Results show the significant impact of highly-exposed population, road length, village density, built-up areas, road category, and multilane roads on pedestrian fatalities, with a positive association.

Conclusions: The study proposes a novel methodology to identify high-risk roads and significant risk factors for pedestrians on high-speed rural roads. It highlights the utility of satellite-derived data for large-scale analysis and the need for pedestrian-centric road designs in rural areas.