ABSTRACT Air navigation is increasingly dependent on the use of Global Navigation Satellite Systems (GNSS). It allows the determination of the aircraft’s position in all phases of the flight and brings many advantages. Although GNSS navigation results in gains, the radio signals from these systems are strongly influenced by the ionospheric environment. It introduces errors that can affect the accuracy, integrity, availability and continuity requirements established by the International Civil Aviation Organization (ICAO). The ionospheric layer has different behaviors depending on the latitude, time of day, season of the year, geomagnetic activity and solar cycle. Since Brazil is located in a region of low latitudes, it experiences a series of unique challenges when compared to regions of mid-latitudes. For this reason, the application of GNSS-based technologies in aviation over the Brazilian territory requires an in-depth assessment of the ionosphere effects. Therefore, the Instituto Nacional de Ciência e Tecnologia (INCT) named GNSS Technology for Supporting Air Navigation was formed in 2017 to better assess the ionosphere impacts and assist government agencies and companies in the development of safe air navigation procedures over Brazil in a near future. This paper presents the most relevant advances achieved so far within this multidisciplinary project that involves Brazilian research centers and universities.

O desenvolvimento tecnológico tem impulsionado a utilização de sensores para a realização de coletas automatizadas e periódicas de dados, como aqueles empregados no Sistema Integrado de Monitoramento Ambiental (SIMA), cujo conjunto de dados é utilizado neste trabalho. Apesar da automatização do processo de aquisição de dados, estes podem apresentar falhas decorrentes de problemas na coleta, na transmissão ou no armazenamento dos dados. A existência de grande quantidade de dados temporais multivariados e a possibilidade de falhas são indicativos da necessidade de utilização de recursos computacionais para apoiar o processo de análise. Neste trabalho são utilizadas técnicas de análise visual para a extração de características do conjunto de dados, as quais, posteriormente, podem impactar a qualidade da análise dos fenômenos associados. Os resultados obtidos demonstram os benefícios da utilização de representações visuais e interativas para a exploração do conjunto de dados, as quais facilitam a percepção de informações acerca de: disponibilidade dos dados; funcionamento dos sensores; e evidências de padrões de falhas.

The technological advances has boosted automated and periodic data collections using sensors, such as those performed in Integrated Environmental Monitoring System (SIMA), which dataset is used in this work. Despite of the automation degree, there are some flaws in the dataset caused by problems in the collection, transmission or data storage. Due to the existence of large multivariate temporal data and the possibility of failure, interactive visual representations of the data can improve the study and characterization of the dataset. In this work, Visual Analytics techniques were applied to obtain some characteristics from the environmental dataset, which subsequently can impact the quality of analysis of the associated phenomena. The results showed the benefits of using visual and interactive representations for dataset analysis, which facilitates the information extraction about dataset characteristics, such as data availability, sensors operation characteristics, and evidences of a failure pattern