Abstract Manager

Transportation is rapidly shifting toward a data-first operating model, where continuously updated digital representations of the public right-of-way form the foundation of municipal mobility systems. Advances in aerial imagery and Computer Vision models now enable transportation networks to be digitized at city scale without field surveys, producing high-definition base layers that remain current as streets evolve. These living digital environments provide municipalities with a reliable foundation for planning, operations, and future mobility initiatives, replacing static datasets with infrastructure-grade data that can support daily decision-making.

Computer vision models trained on hundreds of cities’ transportation networks enable rapid detection with aerial imagery that transforms modern GIS operations. These high-definition transportation maps provide a detailed and consistent representation of the road environment with incredible granularity in attributions, which when combined with live data counts, allows for a one-to-one scale representation of the urban environment in a digital form. For instance, when combined with live traffic sensors, these maps support simulation environments that allow municipal agencies to test scenarios, evaluate corridor strategies, and explore autonomous driving readiness. This intersection of real-time information and high-fidelity base networks creates a foundation for more responsive planning, operations, and investment decision-making.

GeoMate develops high-definition transportation maps and digital road twins that serve as a core data layer for municipal asset management and planning frameworks. By integrating accurate physical networks with dynamic traffic data, cities can move toward connected mobility ecosystems that support transportation planning, traffic operations, emergency services, and future automation. The presentation would include several real-world applications and projects GeoMate has undertaken with municipal planning teams in Canada and globally. AI-based mapping enables cities to better manage growth, support public safety and maintenance programs. With the growing role of AI, building accurate transportation datasets to leverage real-time data is fundamentally transformative for the planning industry, creating transport networks that are more adaptive, resilient, and aligned with community needs