Introducing spatial data science

These materials introduce ‘spatial data science’ or might also be considered a course in ‘advanced GIS’ which is what it was developed to be when it was Geog 315 at Victoria University of Wellington.

I am happy to discuss developing any or all of these materials into short intensive one/two/three day courses to suit the needs of organisations grappling with connecting their geospatial and data analytics workflows.

Content	Hands-on materials
1. Introducing R for geospatial
Open science, open source, and doing GIS in code Starting R	Software setup Introducing R and RStudio
2. Making maps
Choropleth map design Bonus material on zoomed-in maps	Making maps
3. Wrangling spatial data
The myth of tidy data Data wrangling Handling tables Spatial data wrangling	Spatial data manipulation
4. Clustering analysis
Clustering analysis Applications of clustering analysis	Geographic cluster analysis
5. Raster data
Introducing raster data Working with rasters
6. Simple statistical models
From overlay to regression models Regression models More on regression	Building a simple statistical model
7. Where to from here?
Other spatial analysis methods Network analysis Time geography Simulation models	See also Spatial analysis & modelling