PyGeoApi: YIPEEO¶

Connect to PyGeoApi service¶

The YIPEEO vector data is exposed as OGC API - Features accessible via EODC’s PyGeoApi.

Available YIPEEO collections¶

Data set ID	Description	Access Level
pub_yipeeo_yield_fl	Yield estimation and prediction at field level.	Public
pub_yipeeo_yield_nuts2	Yield estimation and prediction at NUTS2 level.	Public
prv_yipeeo_yield_field	Yield estimation and prediction at field level.	Protected
prv_yipeeo_yield_nuts1	Yield estimation and prediction at NUTS1 level.	Protected
prv_yipeeo_yield_nuts2	Yield estimation and prediction at NUTS2 level.	Protected
prv_yipeeo_yield_nuts3	Yield estimation and prediction at NUTS3 level.	Protected
prv_yipeeo_yield_nuts4	Yield estimation and prediction at NUTS4 level.	Protected
prv_yipeeo_fertilize	Data on fertilizer use at field level.	Protected
prv_yipeeo_irrigate	Data on irrigation use at field level.	Protected

The protected collections are only accessible using an EODC account. This tutorial demonstates the use of the OGC API - Features making use to the owslib Python client and the EODC SDK for authentication.

import geopandas as gpd
import contextily as cx
from rich.console import Console

# EODC SDK
from eodc.auth import DaskOIDC

# OWSLIB
from owslib.ogcapi.features import Features

# EODC OGC API URL
EODC_OGCAPI_URL = 'https://features.services.eodc.eu/'

console = Console()

Without Authentication¶

Without Authentication, we can still list all available feature collections, as well as all features from collections which are not protected. But we are not able to read features from protected collections.

# create eodc_ogcapi object without authentication header
eodc_ogcapi = Features(EODC_OGCAPI_URL)
feature_collections = eodc_ogcapi.feature_collections()
console.print(feature_collections)

Try to get items of a protected collection.

collection_id = 'prv_yipeeo_yield_field'

# This will fail with an '401 Authorization required' error code
items = eodc_ogcapi.collection_items(collection_id)

With Authentication¶

To read features from protected collections, you need to authenticate with your EODC credentials. Enter your username, typically the email address you used to sign up at EODC. A password prompt will be opened automatically.

After sucessful authentication, the access token will be used as HTTP header for all future requests using OWSLIB.

# Enter your username, typically the
# email address you used to sign up at EODC
username = "firstname.lastname@eodc.eu" 

conn = DaskOIDC(username)

headers = {
    "Authorization": f"Bearer {conn.token['access_token']}"
}

# add HTTP headers to eodc_ogcapi object
eodc_ogcapi = Features(EODC_OGCAPI_URL, headers=headers)

Print properties of the first item of the given feature collection

items = eodc_ogcapi.collection_items(collection_id)
console.print(items['features'][0]['properties'])

Run a query to extract certain features¶

Query collection prv_yipeeo_yield_field for

common winter wheat (C1111)
winter barley (C1310), and
for a given bounding box near Brno

and we only want to have a subset of all attributes (properties)

bbox = [16.229703926693578,48.713318232352485,17.472665146572798,49.4680057323523]

selected_props = "crop_type,crop_id,yield,c_year"

cql_filter = "crop_type='common winter wheat' OR crop_type='winter barley'"

# get all items in the yipeeo_yield_fl collection
field_items = eodc_ogcapi.collection_items(
    collection_id=collection_id,
    bbox=bbox,
    limit=2000,
    properties=selected_props,
    filter=cql_filter,
)
console.print(f"We found {len(field_items['features'])} items matching the query criteria.")

Convert features into Geopandas DataFrame¶

df = gpd.GeoDataFrame.from_features(field_items["features"], crs="EPSG:4326")
df 

Plot geometries¶

ax = df[["geometry"]].plot(
    facecolor="none", figsize=(12, 6)
)
cx.add_basemap(ax, crs=df.crs.to_string(), source=cx.providers.OpenStreetMap.Mapnik)