Introduction to Programming for GIS and Remote Sensing

This course introduces the theory and applications of both statistical and deep learning-based machine learning methods for supervised learning tasks such as classification, segmentation, object detection, anomaly detection, and change detection for remote sensing data.

Selected Student Projects

Fall 2023

Solar Radiation’s importance on Air Quality by Victor Geiser
A Decade of Evolution in STL by Bishal Roy
An Analysis of Air pollutants and respiratory diseases in California by Imran Said
The City Above the Mines: Development Dynamics in St. Clair by Cagri Gul

Fall 2022

Predicting Atmospheric River Conditions along the West Coast by Ryan Kelly
Predicting Health Inspection Scores in Las Vegas, NV by Alexander Lamb
How do you systematically prevent Land Encroachment? by Varun Venkatesh