Making maps in R

Anyone who knows me knows that my way of learning things is a bit more roundabout than 'sit in class, pay attention, learn'. I need to, in the immortal words of Nancy from Weeds, 'try again, fail better'.

So, when I decided map-making in R was a thing I needed to learn, I took some open data (thank you, Brazilian Institute of Geography and Statistics) and went to town. This is what I did.

I looked for the data relating to MST settlements, quilombos, and indigenous lands. The Landless Movement (Movimento dos Sem Terra – MST) are mostly known due to their occupation of unproductive land that is owned or illegally used by single individuals or companies. However, they also work with the government to find settlements for the families that are a part of the movement.

Quilombos are communities formed by enslaved people who had either escaped or been released. Their members are known as quilombolas. It has only been since the 1988 Constitution that they have had their rights recognised, or their existence for that matter. It is not uncommon to find comments that people are ‘faking’ their quilombo status to gain rights. However, their pathway to achieve community land ownership is even more complex. To ensure their legal standing and protection, quilombos also go through a very lengthy process of accreditation that includes both federal and state governments, and a number of agencies from both.

Indigenous land demarcation in Brazil was due to be completed in 1993, five years after the constitution was put in place. This, of course, hasn't happened. There are 726 indigenous lands in total, representing 14% of the total Brazilian territory. Indigenous lands have different types of categorisations, from the (very lengthy) process of identification through to reserved/approved. Their areas also aren’t necessarily fully occupied – these lands are reserved for the use of indigenous peoples on the basis of their claim to the territory. Their presence might be limited to a few hectares of land as some move from place to place. This is one of the reasons why preservation of indigenous rights to land is also important for conservation efforts. What they face is constant invasion by landowners and illegal gold prospectors. Little has changed in that regard from 500 years ago and now.

Anyway, my goal here was to use open data to map settlements and demarcated land given latitude and longitude and size and without too much trouble. After a lot of googling, mapdata and maps were the packages that came to the rescue as the simplest to use.

Data for MST settlements came from the National Institute of Colonisation and Agrarian Reform (Incra, 2021); for indigenous peoples and quilombolas, the IBGE database on the topic (2019). The MST .csv file has a very confusing heading - I used the pdf to guide me in fixing it and ultimately used the 'fase' or 'phase' variable to map the recognised settlements (identified in the pdf as 7).

The files needed merging with another that had the longitude and latitude coordinates for Brazilian municipalities. I got this from this github. I then joined each base with this, by IBGE code.

I am the first to say that I'm not an expert coder, I'm barely a coder. That's why I'm doing this: because this is something we can all do. The code might not be the prettiest or the most efficient, but it gets the job done. The output looks like this:

Landless Movement settlements

Officially recognised quilombos

Officially recognised indigenous lands

The R environment should look like this:

The markdown file can be downloaded below.

Download PDF • 220KB

The interesting thing about doing something like this is when you look at other maps, ones about deforestation or, alternatively, conservation, and see that these areas line up almost perfectly.

Inequality in land distribution - Brazil - 2020 (Pinto et al., 2020)

Tree cover with losses and gains - Brazil - 2001-2020, Global Forest Watch

Traditional communities and family farming (in fact, the largest producers of food) are the key to a sustainable future. All three groups discussed here have to deal with a constant threat of violence and a gigantic bureaucracy. But the dream of a sustainable future isn’t utopic. It’s at our fingertips, with applied science and understanding of how to use land, how to eat nutritiously, how to respect peoples’ heritage, and how to distribute equitably not just land, but a common goal of a share for everyone. It’s not hard to see where preservation is succeeding and how the presence of peoples who have different goals other than large profit margins can benefit society overall. And we show that by using some chunky coding, a little effort, and pretty pretty colours.

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