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Completed TRL 6 (started at 4, targeting 6)
The Satellite for Natural and Artificial Plumes (SNAP) project aims to detect and classify natural and anthropogenic plumes in real time, which could enable timely tracking of short-timescale events (current solutions rely on post-processing of downlinked data). Specific plume cases can be generalized to any event detectable by computer-vision techniques. SNAP will use gimbaled cameras to identify and track plumes. The data from the cameras (visible to mid-infrared [IR]) will be processed by a trained neural network to quickly identify plumes. Plume properties, location, and images will be determined and downlinked.
Problem Statement Current plume detection and classification solutions rely on post-processing of downlinked data and do not actively track events of interest. Real-time detection could enable real-time tracking of short time-scale events and reduce the amount of data that needs to be downlinked. Specific plume cases can be generalized to any event detectable by computer vision techniques.
Technology Maturation Flight tests are expected to provide real-time plume identification, accurate plume geolocation (with accompanying images/video), and real-time event tracking using neural network image processing within a small satellite (i.e., a 3-unit CubeSat with an instrument weighing approximately 6 kg). The flight tests aim to advance this innovation’s technology readiness level (TRL) from TRL 4 to TRL 6.
Summary of Flight Test
2022-08-03 The Texas A&M SEAK Lab team tested their autonomous plume identification and tracking payload in a high-altitude balloon launch. While technical issues prevented complete mission success, the payload was able to collect images and test its capability to track plumes. The team aims to use the information obtained from this test flight to improve the payload for future test flights and implementation.
2023-05-24 The Satellite for Natural and Artificial Plumes (SNAP), developed by Texas A&M’s SEAK Lab, collected valuable multispectral imagery of Earth’s surface. The SNAP payload functioned close to or at expected performance levels, and shows promise for the development of future technologies. The team’s focus after the flight will be on data analysis and improving the payload for its next mission. The team is grateful to NASA Flight Opportunities and Aerostar for their support of the project.
This project aims to detect and classify natural and anthropogenic plumes in real time, which could enable timely tracking of short-timescale events (current solutions rely on post-processing of downlinked data). Specific plume cases can be generalized to any event detectable by computer-vision techniques. SNAP will use gimbaled cameras to identify and track plumes. The data from the cameras (visible to mid-infrared [IR]) will be processed by a trained neural network to quickly identify plumes. Plume properties, location, and images will be determined and downlinked. This has the potential to benefit NASA missions, the commercial space industry, other government agencies such as the National Oceanic and Atmospheric Administration (NOAA), U.S. Environmental Protection Agency (EPA), and U.S. Forest Service, as well as the nation.
Future Customers
- Real-time plume identification, geolocation, and event tracking
- Fire, pollution, and volcanic activity monitoring for terrestrial and space-based applications - NASA, National Oceanic and Atmospheric Administration, U.S. EPA, U.S. Forest Service missions and research
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