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Unit of Study

Applied GIS and Spatial Data Analytics
UoS Code ITLS6107
Credit points 6
Offered Summer School - Main and Semester 2
Prerequisites None
Prohibitions TPTM6180
Assumed Knowledge
Additional Information This unit assumes no prior knowledge of GIS; the unit is hands-on involving the use of software, which students will be trained in using.
Lectures 6 x 3.5 hr lectures, 6 x 3.5 hr computer labs.
Assessment individual projects (40%); group project (20%); group presentation (10%); final exam (30%)
Description The world is increasingly filled with systems, devices and sensors collecting large amounts of data on a continual basis. Most of these data are associated with locations that represent everything from the movement of individuals travelling between activities to the flow of goods or transactions along a supply chain and from the location of companies to those of their current and future customers. Taking this spatial context into account transforms analyses, problem solving and provides a powerful method of visualising the world. This is the essence of Geographic Information Systems (GIS) and this unit. This unit starts by introducing students to the \\\'building blocks\\\' of GIS systems, including data structures, relational databases, spatial queries and analysis. The focus then moves on to sources of spatial data including Global Positioning System (GPS), operational systems such as smartcard ticketing and transaction data along with web-based sources highlighting both the potential and challenges associated with integrating each data source within a GIS environment. The unit is hands-on involving learning how to use the latest GIS software to analyse several problems of interest using real \\\'big data\\\' sources and to communicate the results in a powerful and effective way. These include identifying potential demand for new services or infrastructure, creating a delivery and scheduling plan for a delivery firm or examining the behaviour of travellers or consumers over time and locations. This unit is aimed at students interested in the spatial impact of decision-making and on the potential for using large spatial datasets for in-depth multi-faceted analytics.