Integration of Remote Sensing and GIS for Origin–Destination matrix estimation in urban areas

Accurate estimation of Origin-Destination (O-D) matrices is fundamental to effective transportation planning. Conventional approaches based on the four-step travel demand model are often time-consuming, data-intensive, and costly, primarily due to their reliance on extensive demographic and socio-economic data. Integrating Remote Sensing (RS), Geographic Information Systems (GIS), and the Global Positioning System (GPS) will be a more efficient and spatially explicit framework for travel demand analysis. This study presents an approach for estimating O-D matrices by establishing a relationship between land-use characteristics and traffic demand. High-resolution CARTOSAT-1 satellite imagery was used to generate updated ward-wise land-use maps for Tiruchirappalli city, Tamil Nadu, India in the absence of recent land-use data. Using GIS-based spatial analysis, land-use categories were quantified and linked to trip generation and trip attraction patterns across sixty wards. Trip production and attraction were estimated based on residential and non-residential land-use proportions, and these estimates were incorporated into a base-year O-D matrix to derive an updated matrix. The resulting O-D matrix was validated through link-level traffic volume comparisons on selected critical road segments. The findings demonstrate that wards with higher residential land-use exhibit greater trip production, while wards dominated by commercial, educational, industrial and public land uses show higher trip attraction. The study highlights the effectiveness of integrating 3S technology in simplifying O-D matrix estimation, reducing data requirements, and supporting cost-effective and reliable urban transportation planning.
Keywords: Land use; Travel demand modelling; O-D matrix; Trip generation