A learning notebook that guides the user on how to generate a deep learning ready dataset from GOES imagery.
The learning objectives include:
- Given a date and time, download the corresponding GOES satellite imagery from AWS
- From the raw GOES imagery, use SatPy to apply a projection then correct and proccess a True Color composite for the Continental US (CONUS)
- Visualize CONUS True Color composite imagery
- Given a location of interest, create a geographically localized image that is appropiately sized for input to a machine learning application
- Visualize machine learning reaedy raw and composite imagery