Geospatial data - data recorded or representing a specific geographic location - are increasingly recognized as a key component in decision making at many levels; from local, regional, and national government, to private companies, not-for-profits, and academia. The ability to collect, store, analyze, and understand geospatial data is key to supporting effective decision making, and requires a suite of software tools to harness all facets of geospatial data. Using the wide range of tools and libraries available for working with geospatial data, it is now possible to transport geospatial data from a database to a web-interface in only a few lines of code. In this hands-on tutorial, we explore some of these libraries and work through examples which showcase the power of Python for geospatial data.
Prof. Farmer is Associate Director of the Center for Advanced Research of Spatial Information (CARSI) and faculty member of GIScience at Hunter Colleage, City University of New York. His research falls under the banner of "complexity in urban systems", and his specific research interests span a wide range of topics in urban and spatial analysis, with a focus on spatial-temporal dynamics, complexity, and spatial interaction. Prof. Farmer has been an active developer in several open source GIS projects.
The event is held in conjunction with the Interdisciplinary Workshop on Geospatial Computing.
Graham Taylor (Guelph)
Colin Robertson (Laurier)
Robert Feick (Waterloo)