GIS Meets HPC big-data data-analysis image-processing gis optimization parallelization gdal opencv data-science cluster gpu unix-environment slurm bash git conda cuda programming python spark sql pip This program covers fundamental GIS concepts and skills using Python's open-source libraries, with a focus on practical applications and scalability in high-performance computing systems. Participants will gain experience in managing, analyzing, and visualizing spatial data. Details This course is designed to provide mentee(s) with practical skills in Geographic Information Systems (GIS) using open-source Python tools. Participants will explore core GIS concepts and techniques, focusing on the application of Python libraries to manage and analyze spatial data. A key component of the course will be learning how to scale up GIS processing by implementing these tools in high-performance computing (HPC) systems. This approach will enhance the capability to handle larger datasets and more complex analyses, making GIS more accessible and integrative with their existing projects. By the end of this course, attendee(s) will have gained proficiency in applying Python to real-world geospatial challenges and scaling their solutions on HPC platforms, enhancing both their analytical capabilities and their ability to contribute to diverse cyberinfrastructure endeavors. Description Familiarity with the basic concepts of GIS and geospatial data. Estimated Completion Date Tue, 10/15/2024 - 14:35 Description Implementing a spatial and spatiotemporal clustering analysis involving HPC systems - a demo project Description Implementing second and final project defined by the mentee. Estimated Completion Date 11/12/2024 Estimated Completion Date Tue, 12/17/2024 - 14:35 Status In Progress MentorMohsen AhmadkhaniSouth Dakota State University MenteeAmira KefiUniversity of Illinois at Chicago