My personal take on the first week of the #30DayMapChallange, a daily social challenge aimed at designing thematic maps every day in November.
Since 2019, the Geographic Information System (GIS) and spatial analytics community have been quite busy each November — thanks to a fun challenge called the #30DayMapChallange. Each year, this challenge has a thematic schedule, proposing a topic that should be the primary directive for map visualisation to be posted on that particular day. While the issues certainly mean a constraint, they also help participants to find mutual interest, share data sources, and express individual styles visually and technologically.
Here, I would like to briefly overview my first week of this challenge, detailing and showing the different maps I created — usually in Python.
In this article, all images were created by the author.
The first day of this challange usually goes for the most simple geometry of them all — points. To create my POI map, I used NASA’s Open Data Portal’s Meteorite Landing data. This dataset contains about 40k observations, which, when placed on a map, show a remarkable correlation with population densities. So either meteorites target inhabited lands, or we have more data on meteorites where there are more people to find them, right?
To create this (interactive) map, I used Python, in particular, Folium.
On the visualization, I sized each dot marker, corresponding to one meteorite, based on its recorded mass in grams, which ranges from 0.01 g to 60,000 kg or 60 tons. By the way, this 60-ton giant Hoba and was found in 1920 in Grootfonteinn, Namibia. Then, I coloured each marker based on the time of its discovery. Fun fact: the first recorded meteorite, Nōgata (472g), was found in Fukuoka Prefecture, Japan, in 861, shortly after the impact. After this observation, there is nothing in the data for centuries in the database. Then, finally, Elbogen came in 1399 (107000.0), and then, Rivolta de Bassi (103.3g) in 1490 and Ensisheim (127000.0g) in 1491. Looking at later periods in the data set, it turns out that 35% of the meteorites were recorded…