Movement and Networks II
Content for Wednesday, November 15, 2023
Now that we’ve chatted briefly about what a network is and how we represent it for analysis, it’s time to take some first steps toward building spatial networks in R. The backbone of most network analysis is igraph, a package that is available for a number of programming languages. There are also a growing number of spatial network packages being developed for R. We’ll introduce a few of those today.
Resources
Network Data in R and Spatial Networks from the Online Companion to Network Science in Archaelogy introduces a variety of approaches for handling and visualizing network data with
Rusing examples from archaeology.CMRnet: An R package to derive networks of social interactions and movement from mark-recapture data by (Silk et al. 2021) describes a package for developing networks from common wildlife sampling techniques.
The
sfnetworkspackage github page provides a variety of vignettes for manipulating spatial network data within thesfframework for spatial objects.
Objectives
By the end of today you should be able to:
Generate an adjacency matrix for network analysis
Calculate network density, centrality, and other common measures
Generate landscape connectivity models using
terraandgDistance