#OpenSource data and #R code for plotting Correlation between highways and densely-populated areas, globally. Example of Haryana (India).
Data: @openstreetmap @nasa

Full Code🔗https://tinyurl.com/hy-pop-roads

Tools: #rstats, #ggplot2, #tidyterra, #osmextract by @rOpenSci

#Maps #OpenSource code to plot correlation between changes in population density (in last 3 decades) and road network, e.g. #Delhi (#India)
Data: @openstreetmap @nasa

Full Code🔗https://tinyurl.com/delhi-pop-roads

Tools: #rstats #ggplot2 #tidyterra #osmextract by @rOpenSci

#dataviz #ClimateAction A facet graph for drought severity (PDSI) in India with #opensource #raster data. And, a neat trick to put facet_grid like strip labels in facet_wrap() and geom_spatraster()

Full Code🔗https://bit.ly/4aF3mRT

Data: https://www.climatologylab.org/

Tools #rstats #ggplot2 #sf #terra #tidyterra

Second post in the "Hillshade, colors and marginal plots with tidyterra" series exploring an approach to annotating marginal plots on a ggplot2 map of a SpatRaster, including longitude and latitude value information #tidyterra

https://dieghernan.github.io/202212_tidyterra-hillshade-2/