Open source software is well established for basic raster and vector data processing, with the Geospatial Data Abstraction Library (GDAL) as one of the most well known tools. Its utilities and application programming interface (API) have become a common standard for data format conversion, reprojection, spatial and spectral subsetting. With its command line interface utilities, GDAL is better suited for the automatic processing of very large amounts of data and for repetitive processing tasks than most of its commercial counterparts. Though GDAL provides an excellent API on which more advanced image processing tasks can be built, not all users have the time or programming skills to get involved such development. In particular within the remote sensing user community, there is a large interest in machine learning techniques applied to remote sensing data.