Michael,
Warning 1: The dataset has several variables that could be identified
as vector fields, but not all share the same primary dimension.
Consequently they will be ignored.
Yes, the driver is super conservative/picky when trying to recognize a
netCDF file as a vector layer, and its heuristics will return in error
if there is any ambiguity.
I've seen similar cases in other files. I presume the driver could be
updated to 1) choose the primary dimension and read the values while
ignore others 2) user-specify the dimension to include, or 3)
user-specify the fields to exclude
I guess option 2 could be reasonable as an open option
For that particular file, I see that the "feature_id" variable
(corresponding to the "feature_id" dimension) has a cf_role =
"timeseries_id" attribute, and that the global metadata has a
featureType = "timeSeries" attribute. So given
https://cfconventions.org/Data/cf-conventions/cf-conventions-1.11/cf-conventions.html#coordinates-metadata
, this seems to be relatively standardized, and in that case the
heuristics could be improve to recognize that the main dimension is
feature_id (probably with a test that the size of the time dimension is
1). As far as I can see/remember, the vector layer support in netCDF
was originally developed for the featureType=point and profile use cases
, so some tuning for timeseries isn't unexpected
Or maybe if detecting that in the set of dimensions there is only one
with > 1 sample and others ones are at 1, consider only the one with > 1
sample
Even
--
http://www.spatialys.com
My software is free, but my time generally not.
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