Thanks for the inquiry. Indeed the blog posts mention 2017 data. In between we updated the example notebooks and the data, but not the blog posts, however, the principle should be the same.
But I have some doubt about the LULC label. In the blog , the sentinel-2 images are in 2017, but in the AWS S3 Cloud Object Storage the images are in 2019, do they use the same ground truth? For the ground truth, I only find 2017 Slovenia land use map in the official website, so if the dataset use 2019 sentinel-2 images and 2017 land use map, will it cause problems?
Regarding the land-cover reference: there is no problem if you use the 2017 data as we don’t expect large changes anyway. We also use the same reference in the latest notebook examples, so this should be fine.
On the website http://eo-learn.sentinel-hub.com/ you can find the
land_use_10class_reference_slovenia.gpkg reference geopackage file, which contains the whole 10 class land cover reference for Slovenia which you should use.
And I can’t find the useful link of the EOPatches for Slovenia 2017 datasets.
Regarding the dataset, the format was also changed a little bit. It is not possible to download the zip file of all the 2019 eopatches, because it’s simply too much data. Instead, the eopatches were uploaded to the bucket (i.e. check example for one patch) and the bucket was made public. So it is possible for you to directly load an eopatch in your jupyter notebook from the S3 link like in the example below:
So all the data should be available via a simple for loop, or something more advanced if you prefer.
Hope this helps, otherwise, let me know of any other issues that you might be having!