Projects
Urban Geo Analytics contributes to international research and consulting projects at the intersection of geospatial AI, street-level imagery analysis, and urban planning. Below are the projects the firm is or has participated in, from European research consortia to client assignments.
WALK-UP4 — Walkability and the Appropriation of Local Key Urban Places through Pedestrian-Friendly Parking Patterns
Horizon Europe — Driving Urban Transitions (DUT) Partnership, 15-minute City Transition Pathway
Running: 2026 – 2029
WALK-UP4 tackles one of the most sensitive obstacles to the pedestrian-friendly 15-minute city: the amount of public space still devoted to parked cars. Rather than treating parking as a purely technical or economic issue, the project approaches it as a spatial, social and ecological system, developing and testing a multi-scalar “pattern language” of pedestrian-friendly parking, from metropolitan Park & Ride systems down to the fine-grained world of sidewalks, greenery and everyday walking experience. Four contrasting cities form the empirical backbone: Amsterdam (ex-post evaluation of a decade of parking removal), Vienna (near-complete removal of on-street parking planned in District 7), Marseille (benchmarking of 40 local centres), and Kaunas (rapid motorisation in Eastern Europe). The project combines historical and policy analysis, AI-based streetscape mapping, space syntax and morphometric analysis, 3D “Urban Parterre” modelling, and urban living labs where residents, businesses and municipal staff co-construct alternative uses of parking space. UGA supports the consortium on AI-based analysis of street-view imagery, building on its SAGAI and UVLM frameworks to assess streetscape conviviality, parking patterns and pedestrian quality across the case-study cities.
Consortium: CNRS – Université Côte d’Azur, TU Wien, Kaunas University of Technology, Vrije Universiteit Amsterdam, the cities of Amsterdam, Kaunas, Marseille and Vienna (District 7).
AI for Last-Mile Analysis in West Bengal
The World Bank
Running: 2026
Slow road movement in Indian cities is not only a peak-congestion problem. It reflects continuous competition for limited road space among vehicles, pedestrians, vendors, and other uses, creating persistent frictions that are especially important for freight in the first and last mile. While truck GPS data can reveal where speed reductions occur, it cannot explain their causes. Street-level imagery provides direct visual evidence, and Vision-Language Models offer a practical way to convert this imagery into structured, planner-ready indicators at scale. The assignment with the World Bank establishes a rigorous and reproducible benchmark for this approach. It includes the development of a freight-friction indicator framework, a quality-controlled benchmark dataset with expert annotations, the evaluation of multiple open-source Vision-Language Models, and fully documented, locally executable benchmarking pipelines. The objective is to validate the methodology before large-scale inference and mapping in subsequent phases. UGA is the sole consultant for the assignment, leading the design of the indicator framework, dataset curation and annotation, model evaluation, pipeline development, and technical reporting.
Client: The World Bank (Transport / Logistics), Washington, DC.
Study area: West Bengal, India.
EMC2 — The Evolutive Meshed Compact City
Horizon Europe — Driving Urban Transitions (DUT) Partnership, 15-minute City Transition Pathway
Running: 2023 – 2026
The 15-minute city has demanding prerequisites in urban form, and the transition is hardest in suburbs and car-dependent peripheries. EMC2 proposes a new model adapted to these contexts: compact urban development organised as corridors along existing main roads, forming a meshed structure across the metropolitan area. Redesigned for pedestrians, these interconnected roads become vibrant, inclusive main streets offering a high quality of stay, a wide variety of mixed uses, and connections to wider-range mobility options, while the suburban fabric within the mesh requires only marginal improvement. The model is assessed in six European case studies (Nice, Lille–Roubaix–Tourcoing, Vienna, Gothenburg, Florence, and Pisa–Lucca–Viareggio) through a triangulated methodology combining geospatial and network modelling, morphometrics, observational usage analysis and planning-oriented evaluation. Within EMC2, UGA designed and developed the project’s AI streetscape-analysis tooling under contract with CNRS: SAGAI, the open-source workflow for VLM-based scoring and mapping of street-level urban scenes, and UVLM, the unified multi-model VLM inference and benchmarking framework.
Consortium: CNRS – Université Côte d’Azur, Agence d’Urbanisme Azuréenne and Agence d’Urbanisme de Lille Métropole (France), Chalmers University of Technology – SMoG and the City of Gothenburg (Sweden), University of Pisa – DESTeC and the City of Viareggio (Italy), and TU Wien – Department of Urban Design (Austria).
WALK-UP4 — Walkability and the Appropriation of Local Key Urban Places through Pedestrian-Friendly Parking Patterns
Horizon Europe — Driving Urban Transitions (DUT) Partnership, 15-minute City Transition Pathway
Running: 2026 – 2029
WALK-UP4 tackles one of the most sensitive obstacles to the pedestrian-friendly 15-minute city: the amount of public space still devoted to parked cars. Rather than treating parking as a purely technical or economic issue, the project approaches it as a spatial, social and ecological system, developing and testing a multi-scalar “pattern language” of pedestrian-friendly parking, from metropolitan Park & Ride systems down to the fine-grained world of sidewalks, greenery and everyday walking experience. Four contrasting cities form the empirical backbone: Amsterdam (ex-post evaluation of a decade of parking removal), Vienna (near-complete removal of on-street parking planned in District 7), Marseille (benchmarking of 40 local centres), and Kaunas (rapid motorisation in Eastern Europe). The project combines historical and policy analysis, AI-based streetscape mapping, space syntax and morphometric analysis, 3D “Urban Parterre” modelling, and urban living labs where residents, businesses and municipal staff co-construct alternative uses of parking space. UGA supports the consortium on AI-based analysis of street-view imagery, building on its SAGAI and UVLM frameworks to assess streetscape conviviality, parking patterns and pedestrian quality across the case-study cities.
Consortium: CNRS – Université Côte d’Azur, TU Wien, Kaunas University of Technology, Vrije Universiteit Amsterdam, the cities of Amsterdam, Kaunas, Marseille and Vienna (District 7).
AI for Last-Mile Analysis in West Bengal
The World Bank
Running: 2026
Slow road movement in Indian cities is not only a peak-congestion problem. It reflects continuous competition for limited road space among vehicles, pedestrians, vendors, and other uses, creating persistent frictions that are especially important for freight in the first and last mile. While truck GPS data can reveal where speed reductions occur, it cannot explain their causes. Street-level imagery provides direct visual evidence, and Vision-Language Models offer a practical way to convert this imagery into structured, planner-ready indicators at scale. The assignment with the World Bank establishes a rigorous and reproducible benchmark for this approach. It includes the development of a freight-friction indicator framework, a quality-controlled benchmark dataset with expert annotations, the evaluation of multiple open-source Vision-Language Models, and fully documented, locally executable benchmarking pipelines. The objective is to validate the methodology before large-scale inference and mapping in subsequent phases. UGA is the sole consultant for the assignment, leading the design of the indicator framework, dataset curation and annotation, model evaluation, pipeline development, and technical reporting.
Client: The World Bank (Transport / Logistics), Washington, DC.
Study area: West Bengal, India.
EMC2 — The Evolutive Meshed Compact City
Horizon Europe — Driving Urban Transitions (DUT) Partnership, 15-minute City Transition Pathway
Running: 2023 – 2026
The 15-minute city has demanding prerequisites in urban form, and the transition is hardest in suburbs and car-dependent peripheries. EMC2 proposes a new model adapted to these contexts: compact urban development organised as corridors along existing main roads, forming a meshed structure across the metropolitan area. Redesigned for pedestrians, these interconnected roads become vibrant, inclusive main streets offering a high quality of stay, a wide variety of mixed uses, and connections to wider-range mobility options, while the suburban fabric within the mesh requires only marginal improvement. The model is assessed in six European case studies (Nice, Lille–Roubaix–Tourcoing, Vienna, Gothenburg, Florence, and Pisa–Lucca–Viareggio) through a triangulated methodology combining geospatial and network modelling, morphometrics, observational usage analysis and planning-oriented evaluation. Within EMC2, UGA designed and developed the project’s AI streetscape-analysis tooling under contract with CNRS: SAGAI, the open-source workflow for VLM-based scoring and mapping of street-level urban scenes, and UVLM, the unified multi-model VLM inference and benchmarking framework.
Consortium: CNRS – Université Côte d’Azur, Agence d’Urbanisme Azuréenne and Agence d’Urbanisme de Lille Métropole (France), Chalmers University of Technology – SMoG and the City of Gothenburg (Sweden), University of Pisa – DESTeC and the City of Viareggio (Italy), and TU Wien – Department of Urban Design (Austria).
