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SDA
Home page for the course Spatial Data Analysis, by Matteo Coronese.
This course introduces foundational and advanced methods for the analysis of spatial data, with a focus on practical implementation in R. It covers core concepts of spatial information such as coordinate reference systems, vector and raster data models, spatial joins, distance measures and visualization techniques. The course examines exploratory spatial data analysis, including spatial autocorrelation and local patterns of spatial association. Building on these foundations, it discusses methods to detect, model and account for spatial dependence in empirical analysis. Through applications to socio-economic and environmental data, participants develop the ability to incorporate spatial structure into quantitative research and to understand its implications for inference and interpretation.
In-person attendance is strongly encouraged, as sessions will include hands-on coding components. A remote participation link will be made available.
Basic knowledge of R and quantitative methods is recommended. No prior background in GIS or spatial analysis is required. Participants are expected to bring their own laptop with a working installation of R and RStudio. For instructions on required packages, see the dedicated page.
- June 8th, 10-13, Aula 4 Sant'Anna Main Building
- June 9th, 10-12, Aula 3 Sant'Anna Main Building
- June 15th, 11-13, Aula 3 Sant'Anna Main Building
- June 18th, 14-17, Aula 3 Sant'Anna Main Building,
To view the slides, just click on the link. To download files R scripts, right-click on the link, and select 'Save link as'.