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# sgillies/advanced_rasterio_features.ipynb Last active Apr 18, 2019

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### chelm commented Dec 18, 2017

 Great write up @sgillies - especially cool is the lazy warping

 +1

 +1

### lbustelo commented Mar 7, 2018

 I'm trying to run rasterio in my notebook setup and keep getting when I import the module. Any pointers? I'm running my notebooks inside a container built based on the official jupyter docker stacks. I basically installing the python-numpy gdal-bin libgdal-dev on top of that image. --------------------------------------------------------------------------- ImportError Traceback (most recent call last) in () ----> 1 import rasterio /opt/conda/lib/python3.5/site-packages/rasterio/__init__.py in () 13 import warnings 14 ---> 15 from rasterio._base import ( 16 eval_window, window_shape, window_index, gdal_version) 17 from rasterio.dtypes import ( ImportError: /usr/lib/libgdal.so.1: undefined symbol: sqlite3_column_table_name 

### lbustelo commented Mar 7, 2018

 Never mind the above... I had and old version of GDAL. After that, I pulled the --pre version of rasterio and was able to get going.

### renelikestacos commented Jul 6, 2018 • edited

 by some reason i am getting error on from rasterio.vrt import WarpedVRT it shows me an import error. ImportError: No module named 'rasterio.vrt' I checked stackoverflow but couldn't find a solution by now. Anyone has the same issue?

### yinniyu commented Nov 5, 2018

 Thanks for sharing this wonderful write up. I noticed that AWS_access_key is required, does that mean the landsat data is requester-pay?

### mwkorver commented Dec 5, 2018

 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

### Dehde commented Jan 18, 2019

 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"