Quantitative assessment of spatial patterns has been a keen interest of generations of spatial scientists and practitioners using spatial data. This post describes Information Theory-based metrics allowing for numerical description of spatial patterns. Each example is accompanied by an R code allowing for reproducing these results and encouraging to try these metrics on different data.
To learn more about this topic, read our open access article:
Nowosad, J., and T.
A few months ago I have made an attempt to visualize the world population changes from 1800 to 2100:
Inspired by @MaxCRoser and @jkottke, I've tried to visualize the world population changes from 1800 to 2100. My new blog post at https://t.co/XpBpkZLO9s describes how this animation was made using #rstats and #OpenData. pic.twitter.com/WI3gj0xUwU
— Jakub Nowosad (@jakub_nowosad) October 9, 2018 This way of visualization is good to show the ever-changing distribution of the population on a global scale.