WebMGS 2017

Diansheng Guo

Diansheng Guo

University of South Carolina

Diansheng Guo

Spatial Data Mining, Geovisualization, and Big Data Analytics—Challenges, Methods and Applications

Spatial and spatiotemporal data analytics plays a major role in this era of Big Data as the majority of data available today are inherently spatial, collected with ubiquitous location-aware sensors such as mobile apps, GPS, census survey, satellites, monitor stations, social media, and geocoded health records. The key to unlock the value of such data lies in the development and application of innovative theories and methodologies to extract information, discover new knowledge and produce actionable solutions from big spatial data. However, it remains a challenging research problem to analyze, visualize and understand complex and dynamic geospatial data, which come in different forms, with various quality issues, for different purposes, and involving many known/unknown factors. In addition to a general overview of challenges and methodologies, this talk particularly focuses on two research topics in big spatial data analytics: (1) multivariate spatiotemporal data analysis, visualization and mapping, and (2) geographic mobility data analysis, modeling, visualization and mapping. For each topic I will present a series of new methodologies (computational, statistical and visual approaches) for the analysis, mapping and understanding of complex spatial or spatial temporal data, accompanied with applications, case studies and web-based software solutions.


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The ISPRS Geospatial Week 2017