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Exercise 7 - Environmental data via OGC API - Environmental Data Retrieval

OGC API - Environmental Data Retrieval provides a Web API to access environmental data using well defined query patterns:

OGC API - Environmental Data Retrieval uses OGC API - Features as a building block, thus enabling streamlined integration for clients and users. EDR can be considered a convenience API which does not require in depth knowledge about the underlying data store/model.

pygeoapi support

pygeoapi supports the OGC API - Environmental Data Retrieval specification by leveraging both feature and coverage provider plugins.

Note

See the official documentation for more information on supported EDR backends

Publish environmental data in pygeoapi

Let's try publishing sample weather forecast model data from NOAA via the EDR xarray plugin. The sample data can be found in workshop/exercises/data/gfs_tmp2m.zarr:

Update the pygeoapi configuration

Open the pygeoapi configuration file in a text editor. Add a new dataset section as follows:

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    noaa-gfs:
        type: collection
        title: Global Forecast System (GFS), 2 metre air temperature
        description: Global Forecast System (GFS), 2 metre air temperature
        keywords:
            - gfs
            - forecast
            - air temperature
        extents:
            spatial:
                bbox: [-128,23,-65,50]
                crs: http://www.opengis.net/def/crs/OGC/1.3/CRS84
            temporal:
                begin: 2023-09-27T18:00:00Z
                end: 2023-09-28T06:00:00Z
        links:
            - type: text/html
              rel: canonical
              title: information
              href: https://www.ncei.noaa.gov/products/weather-climate-models/global-forecast
              hreflang: en-US
        providers:
            - type: edr
              name: xarray-edr
              data: /data/gfs_tmp2m.zarr
              x_field: lon
              y_field: lat
              time_field: time
              format:
                  name: zarr
                  mimetype: application/zip

Save the configuration and restart Docker Compose. Navigate to http://localhost:5000/collections to evaluate whether the new dataset has been published.

At first glance, the Global Forecast System (GFS), 2 metre air temperature (noaa-gfs) collection appears as a normal OGC API collection. Look a bit closer at the collection description (http://localhost:5000/collection/noaa-gfs), and notice the "Data Queries" and "Parameters" sections (add f=json to the collection description URL to inspect the additional EDR specific elements such as data_queries and parameter_names various JSON elements). The "Parameters" section describes the environmental parameters associated with the collection which can be used as part of a collection query.

Try visualizing the following EDR position query (focused on Fort Lauderdale, USA) in a web browser: http://localhost:5000/collections/noaa-gfs/position?coords=POINT(-80.1373%2026.1224). Note the interactive graph displaying the time series of 2 metre temperature data.

Client access

QGIS

QGIS supports OGC API - EDR via the EDR plugin. You can install the plugin directly from the QGIS Plugin Hub, by going to Plugins->Manage and Install Plugins on the top level menu.

You can access the plugin through an entry on the plugin menu.

OWSLib - Advanced

OWSLib is a Python library to interact with OGC Web Services and supports a number of OGC APIs including OGC API - Environmental Data Retrieval.

Interact with OGC API - Environmental Data Retrieval via OWSLib

If you do not have Python installed, consider running this exercise in a Docker container. See the Setup Chapter.

pip3 install owslib

pip3 install owslib

Then start a Python console session with python3 (stop the session by typing exit()).

>>> from owslib.ogcapi.edr import  EnvironmentalDataRetrieval
>>> w = EnvironmentalDataRetrieval('https://demo.pygeoapi.io/master')
>>> w.url
'https://demo.pygeoapi.io/master'
>>> api = w.api()  # OpenAPI document
>>> collections = w.collections()
>>> len(collections['collections'])
13
>>> noaa_gfs = w.collection('noaa-gfs')
>>> noaa_gfs['parameter_names'].keys()
dict_keys(['t2m'])
>>> data = w.query_data('noaa-gfs', 'position', coords='POINT(-80.1373 26.1224)', parameter_names=['t2m'])
>>> data  # CoverageJSON data

>>> from owslib.ogcapi.edr import  EnvironmentalDataRetrieval
>>> w = EnvironmentalDataRetrieval('https://demo.pygeoapi.io/master')
>>> w.url
'https://demo.pygeoapi.io/master'
>>> api = w.api()  # OpenAPI document
>>> collections = w.collections()
>>> len(collections['collections'])
13
>>> noaa_gfs= w.collection('noaa-gfs')
>>> noaa_gfs['parameter_names'].keys()
dict_keys(['t2m'])
>>> data = w.query_data('noaa-gfs', 'position', coords='POINT(-80.1373 26.1224)', parameter_names=['t2m'])
>>> data  # CoverageJSON data

Note

See the official OWSLib documentation for more examples.

Summary

Congratulations! You are now able to publish environmental data to pygeoapi.