Implication of Geo Spatial Data in Urban mobility
Keywords: Mobility, Public transport, Real-time geospatial data, IoT, GIS
Abstract. Urban areas are increasingly challenged by rising population densities, rapid urbanization, limited infrastructure, and the resulting strain on mobility systems. These issues are most apparent in persistent traffic congestion, unreliable public transport services, and adverse environmental impacts. In response, real-time geospatial data has emerged as a transformative tool to enhance urban mobility planning and management. Real-time geospatial data refers to continuously updated, location-specific information collected through various sources such as GPS, sensors, and IoT-enabled infrastructure. This data provides dynamic insights into traffic patterns, transport infrastructure usage, service disruptions, and the movement of people and vehicles. Its real- time nature enables cities to respond promptly to changing conditions, optimize transit operations, and improve commuter experience.
The integration of real-time geospatial data enables a wide range of applications, including traffic flow analysis, dynamic route optimization, public transportation performance monitoring, and infrastructure asset management. It also supports the development of sustainable transport systems by informing decisions related to low-emission zones, non-motorized transport, and multimodal connectivity. Transit agencies can leverage this intelligence to deploy resources efficiently, adjust service schedules, and increase accessibility and reliability. Ultimately, real-time geospatial data is not merely a support mechanism but a foundational component of modern urban mobility systems. By enabling data-driven decision-making, enhancing service efficiency, and improving responsiveness, it empowers cities to build safe, inclusive, and sustainable transportation networks. As urban environments continue to evolve, geospatial intelligence will be essential in shaping adaptive and resilient mobility solutions.
