The access to open government data has been a relevant topic for societies around the world, especially over the last ten years. This paper aims to analyze the indicators of the São Paulo City Observatory (ObservaSampa), confronting them with the ISO 3712x series (sustainable, smart, and resilient cities) standards, to assess if the former meet both open data principles and the ISO prescriptions. Bibliometric analysis, comparative analysis, cluster analysis, and principal component analysis (PCA) were the methods used in this research. From the comparative analysis, 18 indicators were identified as conforming and 41 as partially conforming. Thus, 20% of the ObservaSampa indicators adhere to the ISO standards. The PCA applied to the conforming indicators shows component 1 is related to socioeconomic dimensions, while component 2 refers to social policy, with both appraisals confirmed by cluster analysis. Measuring and presenting city data in compliance with indicator standards is relevant because they open the possibility of comparing different cities. However, there is still a lack of consensus on a common set of indicators to be accommodated within the current ISO standards system.

Road traffic accidents occur daily caused by different factors leading to varying degrees of injury severity. Considering this, many studies have been developed to identify and understand these factors to implement preventive actions. A Decision Tree (DT) is one of the techniques that can generate classifications and predictions by detecting a priori unknown patterns. This study aims to identify the characteristics of municipalities with high and very high fatality rates caused by traffic accidents, using a macro level dataset and a DT algorithm (CART - Classification And Regression Tree). Therefore, macro level data from the municipalities of São Paulo state (Brazil) were used, such as demographic and socioeconomic data, fatality rates and other variables related to traffic. The results indicated the Gross Domestic Product (GDP) as the most important variable, and the municipalities were characterized mainly considering the size of the highway network and vehicle fleet (trucks, minibuses, cars, motorcycles). These characteristics could provide support to the government to plan mitigating actions in municipalities with the highest tendency to high traffic fatality rates.

The road traffic accidents are a worldwide problem that has led several countries and organizations to gather efforts to reverse the current scenario. Annually, it makes millions of deaths, leaving many other people with physical or psychological disturbances. The understanding of scenarios related to non-fatal victims of traffic provides managers improved means to plan and implement preventive actions. Based on indicators and absolute numbers, this work presents the Brazilian scenario of non-fatal victims of traffic accidents. The data indicate that men and young people are the biggest victims, and that each hospitalization costs (on average) to the public treasury more than R$ 1,300.00. The Northeast region as the highest cause for concern, requires immediate action to mitigate damages caused by traffic in their society

In this study, we investigated drivers’ behavior in a highway considering their perception of the quality of service as a function of surrounding traffic conditions, using a driving simulator and an eye tracking system. The driving simulator allows to create different driving environments very similar to real-life driving scenarios. We developed three different scenarios, with traffic densities based on different levels of service, and also prepared a questionnaire to evaluate user perception. Data from the questionnaire, the driving simulator, and the eye tracking system for twenty participants were included in our database. We performed statistical analysis using nonparametric tests (Kruskal-Wallis and Tukey tests) and measured Pearson’s correlation coefficients between variables. Within this preliminary approach, drivers were able to differentiate between the scenarios and were able to determine scores for each level of service presented. These results suggest that driving simulators have considerable potential for the evaluation of quality of service (QoS) perception.

Soil is a strategic resource essential for maintaining ecosystem services, an initiative closely linked to a country’s stage of development. In this sense, urgent strategies are required to mitigate the impacts of climate change on soil systems. This study aimed to assess the susceptibility to soil erosion as a means to support sustainable land-use planning in the municipality of Anápolis, presenting a highly disturbed landscape in Brazil. To achieve this, we applied the Information Value (IV) technique—a Bayesian statistical method based on frequency analysis—which quantifies the influence of various geoenvironmental factors on the probability of erosion occurrence by statistically evaluating their relationship with past erosion events. The results showed that approximately 50% of the municipality is highly susceptible to erosion, and for this reason, these areas should be prioritized by public authorities. The proposed geoenvironmental model demonstrated a satisfactory accuracy (~80%), confirming its effectiveness as a tool to enhance soil resilience.