ProjectLarge-scale and near-term change detection using Remote Sensing
Land-cover change is very important to map because it informs government decisions regarding land-use planning, carbon sequestration, disaster susceptibility assessments, and other land management. My current research explores the use of the Bayesian Updating of Land Cover (BULC) algorithm in rapid and accurate identification of land-cover change. I hypothesize that using Google Earth Engine and BULC, I can improve the temporal frequency and categorical depth of land-cover change classification compared with other common methods. I am interested in applying these techniques to analyze both natural and human land-cover change events such as wildfires, urbanization, logging, etc. Scientific communication and outreach is an additional goal of this project. To address this goal, I am working with a fifth grade teacher to make this science accessible for young scientists of all backgrounds.