Building spatial databases based on co-location

Today we’ll continue our development of attributes (or covariates) in our spatial databases. We’ll look at developing attributes that describe various geographic properties along with joining and subsetting based on locations.

Resources

These chapters are not ‘prerequisite’ reading for the week, but provide a lot of helpful background for determining spatial relations between vector datasets and extracting those into attribute tables for subsequent visualization and analysis.

• The Spatial Data Operations Chapter in (Lovelace et al. 2019) makes the concepts of a network concrete (literally) by using a transportation route example to illustrate the various components of a network analysis in R.

• Attributes and Support of Spatial Data Science, a bookdown project by Edzer Pebesma and Roger Bivand (of the sf, sp, rgeos, and rgdal packages)

Slides

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• Building spatial databases based on attributes
• Workflows for spatial analysis
• Databases and attributes
• Common attribute operations
• Joining (a)spatial data