Comments (1)
One of the challenges to this task is that the cloudmasking algorithm must operate per-scene as several of the operations require global percentiles. So we can't do clipped subsets without biasing the results.
The other option is to do reduced resolution overviews but there could be some bias from resampling and scale issues.
Final option is to write a script to be run on an EC2 instance that pulls full datasets from s3://landsat-pds
, runs the operational test suite. The results could be downsampled/clipped and transferred locally for inspection.
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Related Issues (12)
- pythonfmask HOT 3
- Expose kwargs and options for filter sizes
- Property-based tests
- Reduce memory footprint
- Handle absence of TIRS Band 10
- use of np.fmax with 3 arrays in equations.variability prob HOT 2
- More features? HOT 1
- Error in brightness test
- Implement cloud shadow fill/segmentation/matching approach
- Fails when there are no clear sky land pixels HOT 2
- How to handle potential snow HOT 2
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