One more follow-up question: The datasets that I’m interested in contains subdatasets. I can get the info of a subdataset like this: sub_ds_path = 'HDF5:"/vsis3/prod-lads/VNP02IMG/VNP02IMG.A2021064.2342.002.2021128145323.nc"://observation_data/I04' info = gdal.Info(sub_ds_path) This works fine and finishes in a few seconds. However, when I do the same thing for a different dataset (which contains the geolocation of the dataset above): sub_ds_path = 'HDF5:"/vsis3/prod-lads/VNP03IMG/VNP03IMG.A2021065.2324.002.2021127011303.nc"://geolocation_data/latitude' info = gdal.Info(sub_ds_path) This takes about 2.5 minutes and I can see on my network that Python is downloading data at about 1MB/s the whole time. The info from this subdataset contains a lot of ground-control-points, so I tried setting “showGCPs=False”, but that doesn’t solve it. I’m not sure if it’s really the GCPs that’s causing this (when I save the info as a json, it is about 750kb in size). Any ideas what else can cause this difference in execution time? Regards, Bert |
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