gis

In my first post of 2024, which unfortunately has not been possible before April, I will explain how we can group in the same location several proportional circles. In 2022 I was looking for how to represent the number of heat wave days according to the degree of severity in Spain. I found the solution using the circle packing which is also used in the Dorling cartogram.

A short post on how we can position an outermost territory near the main map or insert an orientation map. In this example we use the typical map of Spain where the Canary Islands are located in the southwest of the peninsula.

A while back I saw Chris Campbell’s global maps from the Financial Times like in this Tweet and I thought I needed to do it in R. In this first post of 2023 we’ll see how we can access the GFS (Global Forecast System) data and visualize it with {ggplot2}, even though there are several ways, in this case we use the Google Earth Engine API via the {rgee} package for accessing the GFS data. We will select the most recent run and calculate the maximum temperature for the next few days.

It is very common to see relief maps with shadow effects, also known as ‘hillshade’, which generates visual depth. How can we create these effects in R and how to include them in ggplot2?

Space-time information is vital in many disciplines, especially in climatology or meteorology, and this makes it necessary to have a format that allows a multidimensional structure. It is also important that this format has a high degree of interchange compatibility and can store a large number of data.