Cities can be characterized as an extremely complex and dynamic environment, which integrates multiple interdependent factors and presents a significant challenge in the development and monitoring of public policies. To deal with this complexity and ensure truly effective policies, data-driven decision-making is essential. Cities produce a large volume of data that is crucial for informing these policies. However, many cities face significant challenges in collecting and analyzing quality data due to a lack of technical and human resources. Furthermore, while tabular data is important, it often fails to capture the complex contextual layers present in the urban territory. Geospatial information provides a deeper and more contextualized understanding of the urban context, enriching the decision-making process and promoting more effective public policies.
Within the complexity of city management, safe and sustainable mobility increasingly stands out as an area demanding special attention, primarily due to the challenge of addressing the issue of premature road traffic deaths and injuries. The World Health Organization (WHO) indicates that more than 1.19 million people die in traffic worldwide every year — in Brazil, there are over 30,000 annual victims.
The Safe System and Vision Zero Approach, which advocate that no death or serious injury in traffic is acceptable, illustrate the complexity of urban mobility. The concept involves several areas of action that must be worked on in an integrated manner, including safe road infrastructure and urban design. Therefore, understanding all layers of the territory is essential for identifying risk areas, planning effective interventions, and monitoring results, ensuring that mobility contributes to building a safer urban environment.
The complexity of cities and the need to deeply understand the various aspects that comprise them make territorial analysis an indispensable component in the data and evidence-based decision-making process. By collecting and using data to identify critical areas, for example, it is possible to effectively propose road safety actions and public policies aligned with the Safe Systems approach. For this reason, the Cordial Institute sought to create a methodology for interpreting the territory to facilitate road safety analyses and offer valuable data-based information. This way, it is possible to directly assist municipalities in developing public policies that promote safer mobility in Brazilian cities.
This methodology, named ‘Structurals’, assumes that the road system is not uniform but divided between intersections and mid-blocks (structurals), each having different interactions in the urban environment. Road intersections, for example, are areas of many encounters between different road users, which can sometimes lead to conflicting situations. These conflicts can result in traffic incidents and, therefore, this dynamic deserves significant attention. On the other hand, mid-blocks have different behaviors, such as increased vehicle acceleration or pedestrians crossing outside designated areas, so it is also important in analyses in a complementary way to intersections’.
The processing of structurals requires a few spatial databases that are commonly developed by municipalities: road blocks, central median/divider (if the road block base does not contain this information), and road axis. With this, it is possible to generate a tool with significant analytical impact using easily processed data from municipalities.
To georeference this dynamic, it is necessary to trace the road axis to identify where they meet (intersections) and where they are continuous (mid-blocks). Using PostGIS, the geospatial data extension of PostgreSQL, both free and open-source, a geospatial processing is performed where perpendicular lines to the roadblock polygons are drawn, meeting at an equivalent geometric distance point. Lines are drawn every meter along the roadblock face, resulting in several points located at the road's central axis. These points are connected by lines forming the road axes. When they intersect, they are identified as a road intersection.
From the geoprocessing, intersection areas are drawn in an open-source Geographic Information System (GIS) program, QGis. These areas are ‘buffers’ created from the points generated by the geometric operations, and have their design adapted if they intersect, not being limited only to the geometric point created by the axis crossing — it is not a simple buffer around each crossing but is dissolved to adapt to the road's morphology. This process identifies a primary characteristic of the road system intersections that can be included in territorial analyses: the intersection profile, or how many approaches each intersection has, making it more or less complex proportional to the number of approaches.
Once the areas considered intersections are established, the street axes not present in this area are extracted and become mid-blocks. In other words, mid-blocks are defined after the intersections' geometric definition, as their geometric opposite.
From the structurals' design, it is possible to pair with all available geographic territorial information. The more data provided by municipalities, the greater the territory's knowledge and the possibility of relating these variables. Each structural has characteristics that make more sense to be deepened. In intersections, traffic lights, bus or cycling infrastructure, road hierarchies, and pedestrian crossings can be paired. In mid-blocks, the road width, road hierarchy, speed limit, electronic surveillance presence, speed reducers, block face length, etc., can be paired.
Pairing information with structurals helps identify profiles of these spaces and create insights into road crashes in Brazilian municipalities. With this pairing, it is possible to analyze the distribution of road events between intersections or mid-blocks and their characteristics, the severity of occurrences, and identify critical points that should be prioritized in public policies. Additionally, it is an essential tool for effectiveness analyses and creating comparison groups for monitoring interventions. For example, with intersection structurals, it was possible to identify crossings with similar characteristics in São Paulo to evaluate whether those that received the "Frente Segura" intervention had a reduction in traffic incidents. The same was done with the "Melhor Uso do Leito Viário (MULV)" interventions carried out in mid-blocks of the city. These and other uses of the structurals can be seen on the publication page of the Brazilian Mobility Panel, from the Cordial Institute.