Spatial data analysis in practice involves an encompassing set of skills that includes manipulation of spatial data, exploration of spatial statistics techniques and use of Geographic Information Systems.In this course students are trained to become users of spatial data analysis techniques. Students will gain a broad knowledge of the diversity of current approaches, which methods are at hand and examples of applications using spatial data analysis in different fields. The 2017s course counts with two renowned scholars:
- Prof Robert Haining, University of Cambridge, UK, author of “Spatial Data Analysis”, Cambridge press and
- Prof Luc Anselin, Director, Center for Spatial Data Science, The University of Chicago, USA (http://spatial.uchicago.edu), responsible for the development of software such as Spacestat, Geoda and PySal.
Spatial data analysis involves exploratory and confirmatory analyses that facilitate and enhance decision making with spatial data. This includes techniques that help visualize data, identify patterns and processes, detect outliers and anomalies, test hypotheses and theories, and generate new spatial data and knowledge. It is therefore not a surprise that spatial data analysis is an emerging field, with advancing technologies and evolving applications that are fundamental for a number of sciences, geography, architecture & urban planning, transportation, criminology, demography, epidemiology and economics, just to name a few. Mobile data and services, from apps, allied to GIS, provide the necessary setting for enhanced analysis of patterns and process over time and space.
For more details, see attached the course description or contact the head teacher.