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STARCOP: Automated and self-improving follow-up verification of detrimental human activity from LEO
Mon, 04/24/2023 - 14:00

Start Date:
2022
Programme:
Discovery
End Date:
2022
Programme Reference:
EISI_I-2022-00380
Country:
United Kingdom
Contractor:
Trillium Technologies
Status:
Closed
Description:
‘STARCOP’ is an initiative to use machine learning and multiple satellites with diverse detection capabilities to quickly detect methane leaks and send notifications in near real-time. In this project Trillium Technologies developed machine learning models to automatically detect methane in hyperspectral and multispectral imagery. Their hyperspectral model (HyperSTARCOP) is able to capture more than 90% of plumes in test data while reducing the false positive rate by 39% when compared to state-of-the-art models. In addition, the activity shows for the first time automatic multispectral approaches that are able to capture large plumes in Copernicus Sentinel-2 data and WorldView-3 data.
Application Domain:
Earth Observation
Technology Domain:
1 - On-board Data Subsystems
6 - RF Subsystems, Payloads and Technologies
Competence Domain:
3-Avionic Systems
5-Radiofrequency & Optical Systems and Products
Keywords:
cognitive cloud computing
methane leaks
Executive summary: