• Forward models can generate and store Lookup Tables (LUTs) and datacubes, allowing you to access and manipulate them flexibly. You can load previous outputs (e.g., an LUT of NRCS for specific inputs), perform mathematical operations, and refine the results.
• Inverse models can access pre-existing LUTs and datacubes for tasks such as training, fitting, parameterization, and post-correction.