Data and code for the paper: "Soil Aptitude for Livestock (SAFL): A Dataset for Brazilian Municipalities"

1. Step 1 (step1.py): Generates an image illustrating how to identify and classify soil composition on a municipality-by-municipality basis. 2. Step 2 (step2.py): Calculates the SAFL index for each municipality and stores the resulting data frame as a `.shp` file in the `output` folder. 3. Step 3 (step3.py): Uses the previously created database to produce a map of Brazil, highlighting the municipalities most suitable for livestock production.