A geo-approach to mechanized agricultural expansion in a tropical region: a case study in Rio de Janeiro

Abstract: Advances in geoprocessing techniques and geospatial data manipulation have optimized natural resources and enhanced environmental services globally. The agricultural sector, traditionally associated with intensive land use, is now benefiting from these technologies, leading to improved productivity aligned with better environmental conditions. Mechanization in agriculture is crucial for optimizing processes like soil preparation, planting, and harvesting. This study introduces a geoprocessing-based methodology to create a mechanization index for agricultural production by integrating land slope, land use, and soil classes using Digital Elevation Models (DEMs) and publicly available spatial data. Applied in Rio de Janeiro State, Brazil, a region with diverse altimetry and land use, this workflow uses open-source tools (QGIS) and Python. The results highlight the potential for expanding mechanizable areas and can guide public and private initiatives. Suitability for mechanization was determined for 7936.82 km², or 18.12%, and 5720.84 km², representing 13.06% of Rio de Janeiro’s territory, depending on, respectively, SRTM and RJ25 data resolution and accuracy.