GIS Meets HPC
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.

Goal 1

Familiarity with the basic concepts of GIS and geospatial data.
Estimated Completion Date
10/15/2024

Goal 2

Implementing a spatial and spatiotemporal clustering analysis involving HPC systems - a demo project
Estimated Completion Date
11/12/2024

Goal 3

Implementing second and final project defined by the mentee.
Estimated Completion Date
12/17/2024

Status

In Progress

Mentor

South Dakota State University

Mentee

University of Illinois at Chicago