Soil Aptitude for Livestock (SAFL): A Dataset for Brazilian Municipalities

Resumo

This database presents a municipality-level Soil Aptitude for Livestock (SAFL) index, designed to measure each Brazilian locality’s suitability for cattle pastures. The index is derived from a combination of georeferenced data sources that capture critical environmental factors, particularly soil type. By processing and standardizing this information in Python, the SAFL index consolidates soil classification details—often overlooked in land-use research—into a single metric suitable for diverse applications. Researchers and practitioners can incorporate the SAFL index into their models to account for the influence of soil-related variables on land-use choices. For instance, it may serve as a control or explanatory factor in econometric panel data, improving the study of phenomena such as agricultural expansion, land-use change, and environmental impacts. Beyond econometric modeling, the dataset offers value for policy planning, risk assessment, and investment decisions by highlighting areas with greater aptitude for livestock activities. The SAFL index and its underlying methodology are intended to be transparent, replicable, and adaptable. Users can modify the index to suit regional or thematic requirements, ensuring broad applicability across disciplines including environmental science, economics, and resource management. By making soil suitability data more accessible and standardized, the SAFL database fills a critical gap in available land-use resources and holds significant potential for advancing research and informing decision-making.