Project Overview

Through an interdisciplinary team of geographic information scientists and computer scientists, this project provides the next generation of scalable and high performance spatial analytical techniques. The main project goal is bridging two worlds: the spatial data management and geospatial analysis libraries that perform complex statistical analysis on geospatial datasets. This requires addressing the existing challenges that have hindered intensive utilization of geospatial data from different sources for more extensive analysis than what is currently supported in big data systems. To achieve this, the project will innovate new computational algorithms and combine them with scalable spatial and spatio-temporal data management techniques for regionalization, polygon-based queries, spatial-aware clustering, computational inference, and more.



NSF logo     Co-PI - NSF Award SES-1831615: RIDIR: Scalable Geospatial Analytics for Social Science Research. PI: Sergio Rey, Co-PIs: Ran Wei, Amr Magdy, Vassilis Tsotras, $1,000,000, 10/1/2018-9/30/2021.