Stack / Mosaic STAC item collections
- Dominant language
- Python
- Stars
- 113
- Forks
- 25
- PR merge metrics
- No merged PRs in 30d
Description
[This STAC blog](https://medium.com/radiant-earth-insights/stac-1-0-beta-1-released-c7abed779d5d) (specifically the section under *Additional Flexibility* - proj:shape and proj:transform) gave me the idea that [gdal vrt](https://gdal.org/drivers/raster/vrt.html) with [vrt mosaicking](https://gdal.org/programs/gdalbuildvrt.html) could be leveraged in intake-STAC to stack and mosaic intake-stac item collections.
Here is a gist showing an example of temporally stacking a single band of Sentinel-2a COGS using this approach: https://gist.github.com/rmg55/1acf804ef1af0c7934b265b3a653a486
A similar approach could also be implemented to mosaic data as well (although I have yet to try it). To apply this feature, the [STAC projection extension](https://github.com/radiantearth/stac-spec/tree/master/extensions/projection) would need to be implemented in the STAC catalog. I could not find any existing work by the Open Data Cube folks on this effort (they were referenced in the blog post mentioned above).
A few questions:
1. Is this the optimum way to stitch together these datasets that are organized in granules/tiled files?
1. Does it seem likely that the projection extension will be incorporated in other catalogs?
1. Is this a feature that would make sense to incorporate directly into intake-stac (if so I would be happy to work on this)?
Tagging @scottyhq and @jhamman
Contributor guide
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Research direction
The issue names no intake-stac files, tests, or entry points to begin with. First resolve with maintainers whether GDAL VRT stacking or mosaicking and the STAC projection extension belong in intake-stac; the issue does not define implementation or completion criteria.
Written by the indexing model from the issue text.
Assessment
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100