Machine Learning Based Algorithms for Global Dust Aerosol Detection From Satellite Images: Inter-Comparisons and Evaluation

This research is supported grants from NASA’s CCST program (Grant No. 80NSSC20K0130) managed by David Considine and the NSF Cybertraining program (Grant No. OAC–1730250). The computational resources are provided by the UMBC High Performance Computing Facility (HPCF) which was supported by the U.S. National Science Foundation through the MRI program (Grant Nos. CNS–0821258, CNS–1228778, and OAC–1726023) and the SCREMS program (Grant No. DMS– 0821311), with additional substantial support from the University of Maryland, Baltimore County (UMBC). See hpcf.umbc.edu for more information on HPCF and the projects using its resources.