GeoDec: A Framework to Effectively Visualize and Query Geospatial Data for Decision-Making

• Published in: IEEE multimedia p. 1
• Main Authors: Shahabi, Cyrus, Banaei-Kashani, Farnoush, Khoshgozaran, Ali, Nocera, Luciano, Xing, Songhua
• Format: Magazine Article
• Language: English
• Published: IEEE 2019
• Subjects: Artificial intelligence; Cities and towns; Computational modeling; Computer graphics; Data visualization; Decision making; Distributed Databases; Distrubuted Query Processing; Geographic Information Systems; H.2 Database Management; H.2.4.m Temporal databases; H.2.8 Database Applications; H.2.8.o Spatial databases and GIS; I.2.10 Vision and Scene Understanding; I.4 Image Processing and Computer Vision; I.5 Pattern Recognition; media semantics multimedia image video processing analysis security face recognition; Peer-to-Peer Databases; Sensor Networks; Spatiotemporal phenomena; Urban planning
• ISSN: 1070-986X; 1941-0166
• DOI: 10.1109/MMUL.2010.1

In this paper, we discuss GeoDec, our end-to-end system that enables geospatial decision-making by virtualizing the real-world geolocations. With GeoDec, first the geolocation of interest is rapidly and realistically simulated and all relevant geospatial data are accurately fused and embedded in the virtualized model. Subsequently, users can interactively formulate abstract decision-making queries in terms of a wide range of fundamental spatiotemporal queries supported by GeoDec and evaluate the queries in order to verify decisions in the virtual world prior to executing the decisions in real world. GeoDec blends a variety of techniques developed in the fields of databases, artificial intelligence, computer graphics and computer vision into an integrated three-tier architecture. We elaborate on various components of this architecture, which includes an extensive, multimodal and dynamic data tier, an efficient, expressive and extensible query-interface tier and an immersive, flexible and effective presentation tier.