Erosion is a global problem which each year reduces the amount of arable land left on Earth. Using erosion prediction models, areas susceptible to erosion can be identified and reinforced but the prediction process can be slow with detailed data source like LidarDEM. Using highly parallel graphical processing units to compute all steps required to predict erosion the calculation efficiency can be significantly improved.
In the RUSLE-model the most time-demanding task is the calculation of a flow accumulation (LS-factor). The LSCL program has been programmed with C++ in OpenCL-framework. The program includes several algorithms to calculate flow accumulation D8, FD8, FFD8 and the new anisotropic algorithm developed in MTT. The new algorithm can topologically sort the elevation data to perform almost ten times faster than previous algorithms. All other parts of the RUSLE computation map perfectly to the GPU architecture and are able to complete in less than a second each for a grids containing 72 million cells.