Scientists from the Johns Hopkins University Applied Physics Laboratory (APL), in Laurel, have made significant progress toward creating the first worldwide, near-real-time inventory of road transportation emissions, contributing a major piece to a larger effort to monitor greenhouse gas emissions on a global scale, known as Climate TRACE.
Climate TRACE, from “Tracking Real-time Atmospheric Carbon Emissions,” is a global initiative to build a tool that will provide a public, independent measure of human-caused greenhouse gas emissions using artificial intelligence (AI), satellite image processing, machine learning and other remote sensing technologies.
Climate TRACE will rely primarily on existing infrastructure — satellites, but also mobility data, drones and land- and sea-based sensors. The tool counts former vice president Al Gore among its chief funders and supporters, and it was honored as one of the top 100 inventions of 2020 by Time magazine.
An APL team has demonstrated for the first time that road-transport emissions can be accurately estimated from satellite imagery. In conjunction with other data sources, including road network data, population data and satellite- and ground-based data on carbon dioxide concentrations, the team was able to use satellite imagery to train and validate machine learning models that can be used to make accurate predictions where direct measurements are not available.
Data from APL’s models are incorporated into the first public Climate TRACE inventory and dashboard, which launched this week. The team’s initial proof-of-concept results were presented at the Institute of Electrical and Electronics Engineers Computer Vision and Pattern Recognition 2021 Conference and published in the conference’s proceedings, earning the award for Best Paper in the EarthVision Workshop track.