issue_comments: 198343073
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/790#issuecomment-198343073 | https://api.github.com/repos/pydata/xarray/issues/790 | 198343073 | MDEyOklzc3VlQ29tbWVudDE5ODM0MzA3Mw== | 1151287 | 2016-03-18T12:57:14Z | 2016-03-18T12:57:14Z | NONE | @fmaussion @jhamman re: projecting coordinates to lat-lng. If you consider the raster cells as independent points, you can project them independently but they will likely not be regularly spaced. With few exceptions, if you need to maintain a regular grid, transforming data between projections will alter the shape of the array and require resampling (GDAL and rasterio call the process "warping" to reflect this). There are decisions and tradeoffs to be considered with the various resampling methods, selecting new extents and cell sizes, etc so it's typically not something you want to do on-the-fly for analyses. I think keeping the xarray coordinates as generic cartesian x-y makes sense, at least initially. Even in many GIS tools, analysis is done on a naive 2D plane and it's assumed that the inputs are of the same projection. I'd recommend doing any reprojection outside of xarray as a pre-processing step (with e.g. |
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