AM Caballero-Rodríguez1, S Anderson-Guerrero2 and OJ Munar-Vivas2 #
1Risaralda Sugar Mill, La Virginia, Risaralda, Colombia
2Colombian Sugarcane Research Center (Cenicaña), Florida, Valle del Cauca, Colombia
Land leveling is a crucial process in sugarcane cultivation in the Cauca River Valley as it plays a vital role in ensuring proper water flow within the fields, reducing fuel consumption for water pumping, promoting shoot emergence, and facilitating other mechanized tasks that can be carried out more quickly and efficiently. Traditionally, land leveling involves the use of high-powered tractors equipped with high-precision topographic survey systems. The topographic survey using a RTK signal uses the same tractor that will later be attached to a scraper for leveling. This process takes about 30 minutes per hectare, with a fuel consumption rate of 22-30 L/ha. The use of LiDAR technology with a DJI Matrice 300 RTK drone was investigated for topographical surveys. This approach is currently operational in two sugar mills in Colombia. The drone-based surveying method has significantly increased efficiency, reducing the time required to just 3 minutes per hectare. Moreover, it eliminates the need for fossil fuels, providing operational, economic, and environmental benefits. To facilitate the processing of LiDAR data, a graphical interface was developed. This interface allows for the conversion of point cloud data from the LAS format to TXT format, which is compatible with terrain design software. A Python tool was created to transform LiDAR point cloud data into TXT files suitable for use with Trimble’s WM Form software. This tool utilizes libraries such as WhiteboxTools and Geopandas in Google Collaboratory. Notably, this tool simplifies the process by eliminating the need for manual input of coordinate points and instead extracts this information directly from the point cloud, reducing the likelihood of errors and streamlining the workflow.