The COVID-19 health emergency is impacting all of our lives, but the living conditions and urban morphologies found in poor communities make inhabitants more vulnerable to the COVID-19 outbreak as compared to the formal city, where inhabitants have the resources to follow WHO guidelines. In general, municipal spatial datasets are not well equipped to support spatial responses to health emergencies, particularly in poor communities. In such critical situations, Earth observation (EO) data can play a vital role in timely decision making and can save many people’s lives. This work provides an overview of the potential of EO-based global and local datasets, as well as local data gathering procedures (e.g., drones), in support of COVID-19 responses by referring to two slum areas in Salvador, Brazil as a case study. We discuss the role of datasets as well as data gaps that hinder COVID-19 responses. In Salvador and other low- and middle-income countries’ (LMICs) cities, local data are available; however, they are not up to date. For example, depending on the source, the population of the study areas in 2020 varies by more than 20%. Thus, EO data integration can help in updating local datasets and in the acquisition of physical parameters of poor urban communities, which are often not systematically collected in local surveys.

The recent efforts dedicated to understanding important features and consequences of city growth have profited from the scaling approach to urban indicators. This kind of analysis can be conveniently used to investigate the impact of geo-economic transformations, like fast urbanization and industrial development, which occurred in continental size countries (e.g., India, China, and Brazil) during the past half-century. Profiting from high quality data, this work explores how scaling relationships among urban indicators are influenced by strong regional heterogeneities in Brazil. It is based on economic, infrastructure and violence related data sets for the time interval 2002-2016. Results indicate that regional specificities related to infrastructure, economic development, and geography have a larger influence on the absolute value of the urban indexes. Regional scaling similarities and differences among Brazilian regions were also uncovered. Interesting enough, the results indicate that the richest and poorest Brazilian regions share similar scaling behavior, despite all huge different local influences. By contrast, the results for the two richest regions, with similar average values of urban indexes and the same kind of local influences have rather different scaling properties. Thus, scaling analysis suggests that distinct political solutions might be necessary to improve life’s quality, even for two regions with similar average values of urban indicators.

Urban sprawl in large Brazilian cities has intensified in recent decades, causing increased demand for urban infrastructure, urban services, and new areas for construction. The central goal of this article is to analyze the characteristics of urban expansion in the Canabrava community and its surroundings, in Salvador, Bahia, Brazil, using census data from 1991 and 2010 produced by the Brazilian Institute of Geography and Statistics (IBGE). One problem addressed was that the limits of the census tracts differed between the analyzed periods.

A expansão urbana vem ocorrendo de forma intensa nas últimas décadas nas grandes cidades brasileiras, ocasionando aumento da demanda por infraestrutura urbana, serviços e novas áreas para construção. O tema central deste artigo é analisar as características da expansão urbana na comunidade de Canabrava e seu entorno, em Salvador, Bahia, Brasil, com uso de dados censitários do IBGE dos anos de 1991 e 2010. Uma problemática tratada foi o fato de os limites dos setores censitários divergirem entre os períodos analisados.