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Our existing collaboration with My NASA Data will naturally progress to the professional level NASA Earth Science Data Systems. Using their tools, we can find historical data to compare to our locally collected data from our airborne devices.
NASA IMPACT who we connected with this year, prototypes tools to support earth observation analysis. Inspired by IMPACT’s prototypes, we anticipate building our own Python tools that will be able to manipulate specifics of our local data such as normalising outliers to match professional-grade satellite data.
What questions might be asked when being a proactive student, and what is their choice of approach to find a solution?
Where is there already knowledge to be built on, and where are there opportunities to seek the possible solution? e.g. are there data signatures present? Can a data flow model tool be built? Can there be normalisation of data e.g. to standardise pixels or distances - if varying data is available?
Through experiential, pair-programmer learning, mentorship may take the navigator-driver routine
Expanding
open science
Earth observations are a key component which facilitates scientific progress. IMPACT prototypes the latest technologies to support new science and applications from Earth observation data.
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