| Grant number: | 18/06107-5 |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |
| Start date: | April 01, 2018 |
| End date: | March 31, 2019 |
| Field of knowledge: | Physical Sciences and Mathematics - Computer Science |
| Principal Investigator: | Pedro Luiz Pizzigatti Corrêa |
| Grantee: | Marina de Oliveira |
| Host Institution: | Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
| Associated research grant: | 16/04982-0 - Enabling Integrated Research through monitoring of biodiversity and climate measurements, AP.ESCIENCE.R |
Abstract The advent of big data brought the need to develop efficient methods and algorithms for knowledge discovery in databases. Particularly, data on atmospheric sciences originate from a variety of platforms, from in situ observations to remote sensing and model outputs, which contribute to enhance the variability and complexity of the datasets. There is a need in the atmospheric science community to develop tools for data visualization, integrating diverse datasets and assisting knowledge discovery. The GoAmazon2014/5 experiment, a collaboration between the US-DoE and several Brazilian institutions, monitored atmospheric conditions at three experimental sites in Amazonia, aiming to access the impact of the Manaus air pollution plume over forested areas. The GoAmazon2014/5 experiment provided a comprehensive and unprecedented dataset in Amazonia, available at public databases maintained by the ARM Climate Research Facility and by the Laboratory of Atmospheric Physics at the University of Sao Paulo (LFA-USP). The development of interactive data visualization environments could help to unveil relationships between meteorological, clouds and air pollution variables, assisting the knowledge discovery of the complex biosphere-atmosphere natural interactions in Amazonia, as well as the impact of anthropogenic activities like biomass burning and urban air pollution. This undergraduate research project aims to explore a set of computational tools in the field of visual analytics applied in the data analysis and knowledge discovery of GoAmazon2014/5 data. | |
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