Urban planners and policy makers often rely on data visualization and spatial data mapping tools to perceive the overall urban trends. The accumulation of historical and real-time urban data from many government and private organizations provides the opportunity for an integrated visual analytic platform. Data management and retrieval for geospatial visualization, correlations, and analysis of multiple data dimensions over a map constitute some of the main challenges when dealing with the heterogeneity of urban data from a variety of sources. In this paper, spatiotemporal aggregation strategies and approaches to accelerate the retrieval of spatial data are presented. The methods are tested on visualizing multivariate urban datasets from two cities in Australia that are aggregated from heterogeneous federated urban data providers. The aggregated spatial or temporal features can be visualized as a choropleth heatmap or extrusion on map. Dynamic spatial window query in our visual analytics tool allows extraction of flat geometry objects optimized through materialized views from a database. Given the robust and scalable orchestration of geometries retrieval, this enables urban planners to perform interactive and dynamic multidimensional visual exploration over a map.
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