The availability of freight for transportation systems, such as railways, can be estimated using Geographic Information Systems (GIS). The analysis presented here examines the potential use of rail transportation for moving sugarcane to processing plants in the state of São Paulo, Brazil.
Sugarcane production and railways in São Paulo
Figure 1 presents the active and inactive railway network in São Paulo State together with sugarcane production by municipality. Of the 296 municipalities crossed by railway lines, 224 municipalities produced approximately 217 million tonnes of sugarcane in 2014. This represents the minimum potential volume of sugarcane that could be served by the railway network.
Figure 1 – Sugarcane production and railways in São Paulo
Sugar mills and railways in São Paulo
The proximity of sugar and ethanol mills to railway corridors helps identify which facilities are best positioned to use rail transport for sugarcane logistics. Figure 2 shows that 30 mills (highlighted in red) are located within 5 km of a railway line, while 67 mills (highlighted in yellow) are located within 10 km.
Figure 2 – Sugar mills and railways in São Paulo
The results provide an indication of the volume of sugarcane that could potentially be transported by rail in São Paulo State and identify the mills that are most suitable for receiving rail-served shipments.
However, additional studies are required to assess the economic feasibility of the investments needed to implement this logistics solution. Factors such as loading facilities, rail infrastructure upgrades, operating costs, transportation rates, and handling equipment must also be considered.
Applications of GIS in rail freight analysis
GIS can support rail freight planning by:
- Estimating potential freight volumes.
- Identifying industries located near railway corridors.
- Evaluating opportunities for modal shift from road to rail.
- Supporting infrastructure investment decisions.
- Mapping logistics corridors and areas of influence.
- Analyzing transportation costs and accessibility.
By integrating production data, industrial facilities, and transportation networks, GIS provides valuable insights into freight demand and logistics planning.
Data Sources and Software
The analyses presented in this article were performed using QGIS and the following datasets:
- Sugarcane Production by Municipality in Brazil
- Brazil Railway Network
- Sugar and Ethanol Mills in Brazil (KML)
- Federative Units of Brazil – 2015
These datasets allow transportation planners and industry analysts to evaluate the relationship between agricultural production, industrial processing facilities, and railway infrastructure, supporting more efficient logistics and transportation strategies.