In landscape ecology, we study interactions between organisms and their surrounding environment. The physical landscape is often quantified using ‘landscape metrics’, for further analyses alongside other sources of data.
My recent lectures are focused on introducing such concepts to landscape architects. While I’ve used FRAGSTATS and other GIS software for teaching in the past, I’ve always struggled with compatibility/licensing issues that just made the whole process really cumbersome.
Recently, I came across this R package called landscapemetrics—I was blown away. I’ve always wanted to introduce people to spatial analyses in R, and to show how a programmatic, reproducible workflow in R can be an excellent alternative to conventional software. This was the tipping point for me… I decided to give it a shot!
This post provides a preview of the workshop content. The workshop is meant to be a follow-up lesson to the Introduction to R series I’ll be conducting next semester.
Workshop outline
Why analyse spatial patterns?
Landscape ecology: Conceptual models
Land cover classification
Landscape metrics
I’ve uploaded the slides and data on Github, so that anyone interested to try out the analysis for themselves will be able to do so. If you’re interested in geospatial analysis, check it out!
Slide deck
This post is also shared on R-bloggers.com.
Citation
BibTeX citation:
@misc{x. p.2020,
author = {X. P. , Song},
title = {Analysing Spatial Patterns of the Landscape},
date = {2020-02-01},
url = {https://xpsong.com/posts/intro2r-spatial},
langid = {en}
}
For attribution, please cite this work as:
X. P., Song. 2020. “Analysing Spatial Patterns of the
Landscape.” February 1, 2020. https://xpsong.com/posts/intro2r-spatial.