COMP 272 - Advanced Remote Sensing

Cross-Listed as GEOG 372

This course introduces students to advanced topics in remote sensing analysis and is directed to students who want to work on a research project of their own choice. Introduction to some advanced remote sensing techniques such as the use of machine learning algorithms in image classification analysis (e.g. Random Forests) and time series analysis will be provided, but ultimately topics will be defined by students’ interest. Advanced remote sensing techniques will be learned using Google Earth Engine (GEE). GEE is a cloud-based geospatial analysis platform that uses JavaScript and that enables large scale processing of satellite and other types of imagery. No previous coding experience is required and given the project-based nature of the class, students can opt to use GEE or another geospatial software for their projects. Students are expected to build a body of literature related to a topic of their choice, lead discussions, analyze data, peer-review other projects, and other steps related to the production of a scientific paper. The ultimate goal is to produce a “research manuscript” by the end of the semester and the majority of the grade will come from completing the steps leading to manuscript production. Prerequisite(s): GEOG 352 Spring semester only. (4 Credits)