Geocomputation

We apply computational theories, methods, tools, and technologies to understand complex spatiotemporal processes and solve geographical problems.

Spatial Database Management: Knowledge of database is a highly desirable skill in GIS to efficiently and effectively store, manage, and access big spatial data for data analytics and geospatial application development. Key research and technical themes include relational and object-oriented database design, query languages and performance, distributed database management system, and heterogeneous data integration.

Programming for GIS: Programming is an essential and a high demand skill in GIS to make tedious GIS tasks easier, faster and more accurate by automating data input/output, data preprocessing, analytical algorithm execution, and visualization. Our department utilizes and offer courses for multiple programming languages for GIS including Python, R, Java, Processing, Javascript, and Structured Query Language (SQL).

High-Performance Computing: Unprecedented amount of geospatial data have been collectively generated everyday via ubiquitously distributed geosensor networks, location aware devices, and social media. High-Performance Computing (HPC), often in the form distributed and/or parallel computing such as cluster computing, grid computing, supercomputing, and cloud computing enables to efficiently and effectively collect, store, process, query, analyze, visualize, model, update, share and integrate big geospatial datasets.

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