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Volunteer Develops Machine-Learning Tool to Identify Rare Clouds
Volunteer Namai Chandra created a machine-learning tool for the NASA-supported Space Cloud Watch project to identify noctilucent clouds. The tool distinguishes these "night-shining" clouds from lower-altitude look-alikes.
Why it matters
It streamlines data collection by allowing volunteers to verify sightings, reducing manual verification workloads for scientists studying atmospheric changes.
The details
- Noctilucent clouds scatter sunlight after sunset and before sunrise.
- The pipeline uses pre-screening, cloud classification, and confidence-based review routing.
- Scientists use these sightings to identify factors influencing long-term weather patterns.
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Key connections
NASA funds Space Cloud Watch
NASA supports the Space Cloud Watch citizen science project.
Space Cloud Watch owns Noctilucent Cloud Detector
Space Cloud Watch received and utilizes the Noctilucent Cloud Detector tool created by volunteer Namai Chandra.
Namai Chandra works at Space Cloud Watch
Namai Chandra is a volunteer with the Space Cloud Watch project.
Chihoko Cullens works at Space Cloud Watch
Dr. Chihoko Cullens is a scientist with the Space Cloud Watch project.
Brentha Thurairajah works at Space Cloud Watch
Dr. Brentha Thurairajah is a scientist with the Space Cloud Watch project.
Noctilucent Cloud Detector is built with Machine Learning
The Noctilucent Cloud Detector pipeline is built with machine learning for image pre-screening and cloud classification.
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Space Cloud Watch uses Noctilucent Cloud Detector
Space Cloud Watch contributors and project scientists use the Noctilucent Cloud Detector to screen and review cloud observations.
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