The snow cover phenology dataset was generated by exploiting the snow product MOD10A1.061 and contains the following variables: first snow day (FSD), last snow day (LSD), yearly averaged snow cover area (SCA), snow cover duration (SCD).
https://doi.org/10.48784/1zvv-nw59
Notarnicola, C. (2024). Snow cover phenology (Version 1.0). Eurac Research. https://doi.org/10.48784/1ZVV-NW59
Collection, Snow cover phenology, FSD, LSD, SCA, SCD, MODIS, MODIS-Terra, Hydrography
CC BY 4.0 NC
eurac research - Institute for Earth Observation |
bartolomeo.ventura@eurac.edu |
Viale Druso, 1 / Drususallee 1, eurac research, Bolzano, Autonomous Province of Bolzano, 39100, Italy |
2000-10-01T00:00:00Z 2023-09-30T00:00:00Z
4326 (4326:EPSG)
Grid
Climatology, meteorology, atmosphere
##### ----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("FSD")
## Search for items in the collection
collection_items = list(catalog.search(collections=['FSD'], max_items=10).items())
print(collection_items)
## Retrieve a list of the first 10 items belonging to a specific collection
item = collection.get_item("FSD2000-1")
#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["FSD"].title)
print(item.assets["FSD"].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("SCA")
## Search for items in the collection
collection_items = list(catalog.search(collections=['SCA'], max_items=10).items())
print(collection_items)
url_basepath = "https://eurac-eo.s3-eu-west-1.amazonaws.com/"
collection_url = url_basepath + "FSD" + "/"
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)
Name | Description | Link | Date published | Category |
---|---|---|---|---|
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 |
STAC guidelines | Documentation to browse and download items of the STAC catalog | Link | Feb. 22, 2024 | STAC |