CORINE Land Cover 2018 (CLC2018), Europe (Raster 100m)
FAIR Overall Score
Abstract
The Corine Land Cover 2018 (CLC2018) dataset is one of the datasets produced within the CORINE Land Cover Program to capture land cover/ land use status for 2018. The Corine Land Cover (CLC) is an European programme, coordinated by the European Environment Agency (EEA), providing consistent information on land cover and land cover changes across Europe. CLC products are based on the photointerpretation of satellite images by the national teams of the participating countries - the EEA member or cooperating countries. The resulting national land cover inventories are further integrated into a seamless land cover map of Europe. The resulting European database is based on standard methodology and nomenclature with following base parameters: - 44 thematic classes in the hierarchical 3-level Corine nomenclature - minimum mapping unit (MMU) for status layers is 25 hectares - minimum width of linear elements is 100 metres - minimum mapping unit (MMU) for Land Cover Changes (LCC) for change layers is 5 hectares. It is provided as 100m raster data here
Keywords
Legal constraints
proprietary
FAIR Overall Score: 77%
| Principle | Score | Earned | Level |
|---|---|---|---|
| Findable | 57% | 4 of 7 | moderate |
| Accessible | 100% | 7 of 7 | advanced |
| Interoperable | 67% | 4 of 6 | moderate |
| Reusable | 83% | 5 of 6 | moderate |
Evaluated by F-UJI web service: Anusuriya Devaraju, & Robert Huber. (2020). F-UJI - An Automated FAIR Data Assessment Tool. Zenodo. https://doi.org/10.5281/zenodo.6361400
Snippet code
##### ----Explore and download STAC data with Python ----- #####
from pystac_client import Client
## Read the example catalog
URL = 'https://stac.eurac.edu/'
catalog = Client.open(URL)
## List the Collections in the given Catalog
stac_collections = list(catalog.get_collections())
print(f"Number of collections: {len(stac_collections)}")
## Print collection IDs
print("Collections IDs:")
for collection in stac_collections:
print(f"- {collection.id}")
print("-------------------------")
## Retrieve a specific collection
collection = catalog.get_collection("ID_OfTheCollection")
## Search for items in the collection
collection_items = list(catalog.search(collections=['ID_OfTheCollection'], max_items=10).items())
print(collection_items)
## Retrieve a list of the first 10 items belonging to a specific collection
item = collection.get_item("NameOfTheItem")
#print(list(item.assets.items())[0:10])
##Print the band name and the href of a specific item retrieved from the previous list
print(item.assets["ID_OfTheCollection"].title)
print(item.assets["ID_OfTheCollection"].href)
## Print Item’s assets through the assets attribute, which is a dictionary
for asset_key in item.assets:
asset = item.assets[asset_key]
print("{}: {} ({})".format(asset_key, asset.href, asset.media_type))
## ------------- DONWLOAD COG files from a specific collection ------- ####
from pystac_client import Client
import requests
## Read the example catalog
URL = 'https://stac.eurac.edu/'
catalog = Client.open(URL)
## List the Collections in the given Catalog
stac_collections = list(catalog.get_collections())
# print(f"Number of collections: {len(stac_collections)}")
## Print collection IDs
print("Collections IDs:")
for collection in stac_collections:
print(f"- {collection.id}")
print("-------------------------")
## Retrieve a specific collection
collection = catalog.get_collection("ID_OfTheCollection")
## Search for items in the collection
collection_items = list(catalog.search(collections=['ID_OfTheCollection'], max_items=10).items())
print(collection_items)
url_basepath = "https://eurac-eo.s3-eu-west-1.amazonaws.com/"
collection_url = url_basepath + "ID_OfTheCollection" + "/"
print(collection_url)
for item_id in collection_items:
# item = item.assets[asset_key]
print(item_id.id)
cog_file = str(item_id.id + '.tif')
url = collection_url + cog_file
response = requests.get(url)
with open(cog_file, "wb") as f:
f.write(response.content)
Related docs
| # | Name | Description | Link | Date published | Category |
|---|---|---|---|---|---|
| 1 | MOOC Cubes and Clouds | Free Online Course teaching the concepts of data cubes, cloud platforms and open science in geospatial and EO. | Link | March 8, 2024 | OpenEO, STAC |
| 2 | STAC guidelines | Documentation to browse and download items of the STAC catalog | Link | Feb. 22, 2024 | STAC |