Building networks from spatial data
Today we’ll be exploring one additional data model for spatial information, the network. We’ll explore what constitutes a network, generally. Then, we’ll think a bit about spatial networks. Finally, we’ll start to look at how we might build networks from geospatial data in R.
Resources
These chapters are not ‘prerequisite’ reading for the week, but provide a lot of helpful background for raster proccessing in R.
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Exploring complex networks(Strogatz 2001) is probably one of the most widely read articles describing networks and their role in a broad suite of disciplines. It is also written by a mathemetician which may make some of the language and formulae a little dense for you. That’s okay! Try to take the high-level points and leave the details for now.
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This editorial(Poisot et al. 2016) is the opening to a Special Feature in Functional Ecology and provides some context for networks that are specific to ecologists.
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The Transportation 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.
Slides
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Lovelace, R., J. Nowosad, and J. Muenchow. 2019. Geocomputation with R. CRC Press.
Poisot, T., D. B. Stouffer, and S. Kéfi. 2016. Describe, understand and predict: Why do we need networks in ecology? Functional Ecology 30:1878–1882.
Strogatz, S. H. 2001. Exploring complex networks. nature 410:268–276.