In partnership with Environment Canada through our Data Core program, we created a computer vision model to track bird migrations across Canada. Data from recent years show a decrease in bird populations across North America, prompting interest in studying their migration patterns and habitats.
Timely reliable damage assessment of buildings and infrastructure in the wake of natural disasters is crucial for organized response and recovery efforts. To aid this effort, this project leverages modern machine learning techniques to rapidly analyze the before and after satellite images of affected areas to assess damage.
Reddit Map is an open-source tool that makes navigating Reddit data easier by displaying clusters of communities with overlapping community members.
When whales are encountered near the surface of the ocean, it’s useful to be able to quickly assess their health for conservation and evaluation purposes. As part of our Data Science for the Common Good program, Master’s students Chhandak Bagchi and Gizem Cicekli developed a tool for identifying a whale from an aerial image.
In partnership with the World Resources Institute, a global research organization that works on issues such as energy efficiency and climate change, we examined vehicle usage in developing countries. There is often a lack of critical data for developing countries on vehicle purchases and usage patterns, which is a significant gap in sustainability research.
The Nature Conservancy (TNC) team devised a tool using a computer-vision algorithm to automatically detect whether or not a photograph contains an animal.