Changing Dataset CRS #758
Changing Dataset CRS #758
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This is looking good overall @gkahiu, I think this is on the right track. One additional comment beyond those inline in the review: changing the CRS in settings breaks the code used to filter layers by their extent for the dropdowns in, for example, the "Indicator for SDG 15.3.1" tool. To address this issue the functions called within get_usable_datasets in data_io.py will need to be modified. Right now if you run a "Sub-indicators for SDG 15.3.1" job with a different CRS than WGS84, and then try to run "Indicator for SDG 15.3.1" to integrate them, the dropdowns are all empty, even though data should be available and listed in that tool.
| @@ -175,14 +176,19 @@ def __init__( | |||
| self.out_res = out_res | |||
| self.out_data_type = out_data_type | |||
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| # TODO: Confirm if this should be optional and if we should have | |||
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Yes, we should default to WGS84. Using WGS84 would be consistent with past behavior of the plugin so reasonable to use it as a default.
| self.iface.showOptionsDialog(currentPage=OPTIONS_TITLE) | ||
| self.iface.showOptionsDialog(self.iface.mainWindow(), currentPage=OPTIONS_TITLE) | ||
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| def _validate_crs_multi_layer(self, layer_defn: list) -> bool: |
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It would be worthwhile to offer users an option to automatically reproject any layers that are in a CRS other than that chosen in their user settings. Otherwise there is no easy way for a user to user layers they may have produced in a different CRS (within Trends.Earth that is), without re-running the analysis. Of course there might be boundary effects, due to the reprojection, there might not be transformations among the CRS if they were user defined, etc., but worth offering it as an option if possible.
| resample_mode = self.get_resample_mode(temp_vrt) | ||
| out_res = None # self.get_out_res_wgs84() | ||
| resample_mode = ( | ||
| gdal.GRA_NearestNeighbour |
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This changes the logic - in past versions of T.E. get_resample_mode was used to use either gdal.GRA_Mode for resampling categorical data or gdal.GRA_Average for continuous data when aggregating pixels to go from higher to lower resolution. Better to retain that logic here rather than always use gdal.GRA_NearestNeighbour
Hi @azvoleff,
Please see the work related to #717.
For remote tasks, there is a
crskey added in params that contains the CRS in WKT format using the legacyWKT1_GDALflag. See more options here which are dependent on the version of the Proj library.For locally run tasks, the system now validates whether the input layers are in the same projection as that defined in settings. Also, the
AOIobject fromareaofinterest.prepare_area_of_interestnow uses the CRS from settings. This (AOI) object is cascaded to the respective algorithms.On supporting importation of datasets, this is not fully implemented as it is dependent on PR #757 but have attempted to refactor some of the sections that explicitly used WGS84. One question is to how to handle the respective input and output resolution computations since there will be no CRS conversion to WGS84 taking place as was the case before.