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In past years, geoinformation has gained a significant role in information technology due to the spread of GPS localization, navigation systems and the publication of geographical data via Internet. The inclusion of semantic information and temporal alteration has also become increasingly important in GIS. The overwhelming amount of spatial and spatiotemporal data resulted in increased research effort on processing algorithms and efficient data management solutions. This article presents the AEGIS framework, a currently developed spatio-temporal data management system at the Eötvös Loránd University, Faculty of Informatics (ELTE IK). This framework will serve as the future platform of GIS education and research at ELTE IK. It aims to introduce a data model for the uniform representation of raster and vector data with temporal references; to enable efficient data management using specialized indexing; and to support internal revision control management of editing operations. The framework offers a data processing engine that automatically transforms operations for distributed execution using GPGPUs, allows fast operations even with large datasets and high scalability with regard to new methods. To demonstrate the usage of the system two prototype applications – segment-based image classification and agent-based traffic simulation – are also presented.
"AEGIS - A state-of-the art component based spatio-temporal framework for education and research,"
Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings: Vol. 13, Article 10.
Available at: https://scholarworks.umass.edu/foss4g/vol13/iss1/10