Global Development&Environment
- Teacher: Alexander Kwame Adovor Tsikudo
- Teacher: Mishel Milagros Melendez Bernardo
- Teacher: Nina Roberts
Cities of the World
- Teacher: Sian Butcher
Social & Environmental Issues
- Teacher: Alexander Kwame Adovor Tsikudo
- Teacher: Nikolai Alvarado
- Teacher: Yilun Zhao
- Teacher: Tony Wang
Individual Study
- Teacher: Warren Lavey
CyberGIS & Geospatial Data Sci
- Teacher: Anand Padmanabhan
Dear students,
Greetings, and Welcome to GEOG 479 - High-Performance Geospatial Computing!
Overview.
In this class, you will have the opportunity to learn high performance computing using python to understand computational bottlenecks and produce faster and scalable solutions. For this online course, I will send you a weekly communication (at a minimum) introducing the week's theme, and an introduction to the workload for the week. I will upload any relevant PDF course notes (lectures) that correspond to each week's material.
Class format.
This is the first time that we deliver GEOG 479 online. We will "meet" twice every week through Zoom. Every Zoom meeting starts at 2:00 PM and finishes at 3:20 PM (Monday and Wednesday). During the Zoom meeting, we will discuss major concepts, go through major steps of labs/exercises and address any technical issues. You are expected to complete lab assignments offline.
Software and textbook.
We will be mainly using Python Jupyter Notebook and ArcGIS Pro. Please send me an email if you have trouble installing them or have not used them before.
Supplementary Textbook
- Tang, W., & Wang, S. (2020). High Performance Computing for Geospatial Applications. Springer International Publishing. ISBN: 9783030479978
- Gorelick, M., & Ozsvald, I. (2020). High Performance Python: Practical Performant Programming for Humans. O’Reilly Media. ISBN: 9781492054979
Feel free to email me if you have any questions. Look forward to facilitating your learning in the the fall semester.
- Teacher: Tony Wang
This course is intended to introduce students to geospatial visualization and visual analytics as well as the state-of-the-art of cartographic mapping and visualization technologies in the context of cyberGIS (cyber geospatial information science and systems) and geospatial data science. Students will learn open source mapping and visualization libraries such as Leaflet, D3 and Plotly and how to mash up these libraries to create interactive and dynamic visualization tools and GIS applications. Students are expected to learn how to visualize not only geospatial data but also results of spatial analysis. Emphasis is placed on learning the cutting-edge advances of geospatial visualization and visual analytics and practical skills to create geospatial applications based on such advances.
- Teacher: Su Yeon Han
- Teacher: Ziqi Li
- Teacher: Ziqi Li
- Teacher: Shaowen Wang