Parallelized LEDAPS method for Remote Sensing Preprocessing Based on MPI

Based on Landsat image, the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) uses radiation change detection method for image processing and offers the surface reflectivity products for ecosystem carbon sequestration and carbon reserves. As the accumulation of massive remote sensing data, the traditional serial LEDAPS for image processing has a long cycle that make a lot of difficulties in practical application. For this problem, this paper design a high performance parallel computing method based on MPI. Research and experiment show that the highest speed ratio reached 7.37 when the number of MPI process is 8. The method not only greatly improves the calculation speed and save computing time, but also realize the load balance between the computing nodes and the computing nodes can be extended. It effectively improves the ability of LEDAPS to handle massive remote sensing data and reduces the forest carbon stocks calculation cycle by using the remote sensing images.