issue_comments: 211045128
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https://github.com/pydata/xarray/issues/790#issuecomment-211045128 | https://api.github.com/repos/pydata/xarray/issues/790 | 211045128 | MDEyOklzc3VlQ29tbWVudDIxMTA0NTEyOA== | 2002703 | 2016-04-17T15:38:03Z | 2016-04-17T15:38:03Z | CONTRIBUTOR | In a past life I made side library that wraps rasterio's API to take and return My most common use case was reading disparate rasters and aligning them to the same grid:
1. Use rasterio to load separate spatial rasters over roughly the same area; let's say one is 30-meter satellite and one is 3-meter agricultural yield. Often I'll immediately wrap them in an xarray.DataArray and persist the CRS and affine transform as attributes.
2. Clip the fine-resolution yield array to my area of interest. I can either use
Reprojecting or clipping after reading xarray, like I do, goes against @perrygeo's recommendation. So maybe my example is moot, but I really like being able to do this programmatically in python, not CLI. Even if xarray's new rasterio backend only provides a reader (and not However, if you both expose the transform and realize the coordinate variables, it's possible for them to diverge as the single source of truth. In my above workflow, anytime I clip (step 2) or warp (step 3) data, my side library needed to manually re-set that DataArray's transform and coordinate variables. (This is surely out of scope for rasterio or xarray!) |
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