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NASA Satellites and Data Fusion: A Case Study with Coral ReefsAs the world is experiencing a significant rise in both AI, Climate, and Space start-up companies, we are in a new wave of limitless innovation. NASA's statutory responsibility is to "provide for the widest practicable and appropriate dissemination of information concerning its activities and the results thereof." (51 U.S.C. § 20112) In particular, through machine learning, the public data drawn from NASA’s space assets can provide insights for addressing climate-related problems here on Earth. And many climate start-up companies can benefit from leveraging this data, either for proof of concepts or their own missions. In the Fall of 2021, several scientists from NASA and Coral Vita led a Practicum with the Georgia Institute of Technology Masters in Data Analytics program. The Practicum saw two teams of students develop and implement machine learning models to infer, from CALIPSO satellite imagery, vitality properties upon satellite pass. This kind of capability can lead to real-time mapping of coral health around the world, giving organization an understanding of where to prioritize reef reconstitution.. In this presentation, we will highlight this use case and discuss other concrete applications in which space data is used to solve problems here on Earth.
Document ID
20220007438
Acquisition Source
Langley Research Center
Document Type
Presentation
Authors
Newton Campbell
(Science Applications International Corporation (United States) McLean, Virginia, United States)
Date Acquired
May 12, 2022
Publication Date
May 20, 2022
Publication Information
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: United States Patent and Trademark Office Technology Centers 2100, 2400 and 2600 Tech Fair
Location: Arlington, VA
Country: US
Start Date: May 9, 2022
End Date: May 20, 2022
Sponsors: United States Patent and Trademark Office
Funding Number(s)
CONTRACT_GRANT: NNX16MB01C
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
NASA Technical Management
Keywords
Earth Sciences
Data Fusion
Data Alignment
Machine Learning
Coral Reefs
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