Open vincentsarago opened 3 years ago
sample: https://gist.github.com/vincentsarago/d5091ff44ea6a0a405c3e486c69ffbf4 code: https://github.com/developmentseed/public-datasets/blob/main/public_datasets/feeder/public_datasets/feeder/landsat/aws.py#L198-L302
@sharkinsspatial @geospatial-jeff could you give this a 👀 🙏
lgtm, csv.DictReader
might make parsing the csv easier https://docs.python.org/3/library/csv.html#csv.DictReader. Also I'd recommend lowering the precision of the various float types throughout the item.
I'd personally use Pandas in this situation, and I think it would be faster to use the Pandas chunked CSV reader, but maybe that's too large of a dependency? It might be more relevant for Sentinel because there's more to do
yeah if we can avoind any fancy
dependency it will be better. We don't really need pandas for the Landsat creation because we only need to process one line at a time and don't really need to do operation on a full dataset... which might be the case for Sentinel!
Edit/Note: right now we have rasterio deps but it could easily go!
Given that creating items is mostly a one-time pipeline, I don't have any aversion to fancy dependencies if it makes our life easier
As a minimal input we have to create the scene geometry using the landsat WRS geometry
Data
s3://landsat-pds/c1/L8/scene_list.gz
USGS: https://www.usgs.gov/core-science-systems/nli/landsat/bulk-metadata-service
Links