https://video.osgeo.org/videos/watch/44b4ee45-e9ef-4360-a9c1-265515665914 Cities are extremely complex and dynamic environments, integrating multiple interdependent factors and posing challenges to the development and monitoring of public policies. To ensure effectiveness, data-driven decision-making is essential. Cities generate large volumes of data, but many face difficulties in collecting and analyzing quality information due to limited resources. While tabular data is valuable, it often fails to capture the layered complexity of urban territories. Geospatial information provides a more contextualized view, enriching decision-making and promoting more effective public policies. Within city management, safe and sustainable mobility demands special attention, mainly due to the high number of premature road traffic deaths and injuries. According to the World Health Organization (WHO), more than 1.19 million people die annually in traffic worldwide; in Brazil, over 30,000. Approaches such as the Safe System and Vision Zero, which state that no death or serious injury is acceptable, illustrate this complexity. Their implementation requires integration across multiple areas, including infrastructure and urban design. Understanding territorial layers is crucial for identifying risk areas, planning interventions, and monitoring results, ensuring mobility contributes to safer cities. Territorial analysis becomes indispensable in data-based decision-making. By collecting and cross-referencing information, it is possible to identify critical areas and propose effective actions. To support municipalities, the Cordial Institute developed a methodology called Structurals, aimed at interpreting the road system to facilitate road safety analyses. The method assumes that the system is divided into intersections and mid-blocks, each with distinct dynamics. Intersections concentrate encounters between different users, often leading to conflicts. Mid-blocks involve behaviors such as vehicle acceleration or pedestrian crossings outside designated areas. Both demand complementary attention. Processing structurals requires basic municipal spatial databases: road blocks, medians (if not included), and road axes. Using PostGIS, the open-source geospatial extension of PostgreSQL, a road axis is traced by generating central points along block faces and connecting them. Where axes intersect, intersections are identified. These are represented in QGIS by creating “buffers” around the crossing points, later dissolved to adapt to road morphology. This enables analysis of intersection profiles, such as the number of approaches, which influences their complexity. Once intersections are defined, remaining street segments are classified as mid-blocks, their geometric opposite. From these structurals, municipalities can pair geographic and contextual data. For intersections: traffic lights, crossings, bus or cycling infrastructure, and hierarchy. For mid-blocks: width, hierarchy, speed limits, surveillance, speed reducers, and block length. Pairing these variables enables identification of structural profiles and supports insights into road crashes. Analyses can address distribution of incidents between intersections and mid-blocks, their severity, and location of critical points. This also facilitates impact evaluation and comparison groups for monitoring interventions. For instance, in São Paulo, structurals helped identify intersections with similar characteristics to assess the “Frente Segura” program, as well as mid-blocks that received “Melhor Uso do Leito Viário (MULV)” interventions. Results showed reductions in traffic incidents, demonstrating how structurals contribute to evidence-based urban mobility policies. By offering municipalities a structured approach to integrate geospatial analysis with road safety data, structurals enhance the ability to design, prioritize, and evaluate public policies, supporting safer and more sustainable urban environments. Luis Fernando Villaça Meyer, Beatriz Gonçalves Sun, 31 May 2026 09:47:12 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://video.osgeo.org https://video.osgeo.org/lazy-static/avatars/de841c88-3a57-45ac-9eff-a00237356bfc.png https://video.osgeo.org/videos/watch/44b4ee45-e9ef-4360-a9c1-265515665914 All rights reserved, unless otherwise specified in the terms specified at https://video.osgeo.org/about and potential licenses granted by each content's rightholder.