Towards generating a traffic slowness geospatial dataset of São Paulo city
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Abstract
The city of São Paulo is known for its extensive fleet of vehicles, which, combined with extreme precipitation and flooding events, makes traffic increasingly chaotic. The present work comprises an extracting, transforming and loading (ETL) process to generate a database of 2019 traffic slowness in São Paulo integrated with variables that may influence traffic, such as rainfall, floods, accidents and socioeconomic features. This dataset is expected to support more profound analysis and help in better traffic planning and decision-making.
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English
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Proceedings of the Brazilian Symposium on GeoInformatics, p. 411-416.
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