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Save sgillies/7e5cd548110a5b4d45ac1a1d93cb17a3 to your computer and use it in GitHub Desktop.
First of all, thanks for the great introduction!
2 Questions:
1.What about GeoTIFFs that are striped instead of tiled? Is it still possible to access a subcrop efficiently?
2. Unfortunately the "with rasterio.Env(CPL_CURL_VERBOSE=True)" changes nothing in the output for me. I'm working on windows with rasterio.version = 1.0.8. Any ideas how I could achieve the verbose output? Been stuck on that for a bit..
Maybe interesting for other windows users: I got an SSL error when trying to access the landsat images. I got rid of it by exposing my SSL certificate with:
import os
os.environ["CURL_CA_BUNDLE"] = r"C:\path\to\curl-ca-bundle.crt"
This is fantastic. I have been attempting to figure out how to manipulate LANDSAT and Sentinel data from AWS without downloading wholesale and without using packages like eo-learn and GEE (too hard to customize for my liking). Had seen these features in rasterio but never knew how they worked. This is a well-done write up, cheers.
jg
Landsat 8 on AWS is not requester-pays.
That is why this works.
http://landsat-pds.s3.amazonaws.com/c1/L8/139/045/LC08_L1TP_139045_20170304_20170316_01_T1/LC08_L1TP_139045_20170304_20170316_01_T1_B5.TIF.ovr