Publishing vector data to OGC API - Features

OGC API - Features provides geospatial data access functionality to vector data.

To add vector data to pygeoapi, you can use the dataset example in Configuration as a baseline and modify accordingly.

Providers

pygeoapi core feature providers are listed below, along with a matrix of supported query parameters.

Provider

properties (filters)

resulttype

bbox

datetime

sortby

properties (display)

CQL

CSV

results/hits

Elasticsearch

results/hits

GeoJSON

results/hits

MongoDB

results

OGR

results/hits

PostgreSQL

results/hits

SQLiteGPKG

results/hits

SensorThingsAPI

results/hits

Below are specific connection examples based on supported providers.

Connection examples

CSV

To publish a CSV file, the file must have columns for x and y geometry which need to be specified in geometry section of the provider definition.

providers:
    - type: feature
      name: CSV
      data: tests/data/obs.csv
      id_field: id
      geometry:
          x_field: long
          y_field: lat

GeoJSON

To publish a GeoJSON file, the file must be a valid GeoJSON FeatureCollection.

providers:
    - type: feature
      name: GeoJSON
      data: tests/data/file.json
      id_field: id

Elasticsearch

Note

Elasticsearch 7 or greater is supported.

To publish an Elasticsearch index, the following are required in your index:

  • indexes must be documents of valid GeoJSON Features

  • index mappings must define the GeoJSON geometry as a geo_shape

providers:
    - type: feature
      name: Elasticsearch
      data: http://localhost:9200/ne_110m_populated_places_simple
      id_field: geonameid
      time_field: datetimefield

This provider has the support for the CQL queries as indicated in the table above.

See also

CQL support for more details on how to use the Common Query Language to filter the collection with specific queries.

OGR

GDAL/OGR supports a wide range of spatial file formats, such as shapefile, dxf, gpx, kml, but also services such as WFS. Read the full list and configuration options at https://gdal.org/drivers/vector. Additional formats and features are available via the virtual format, use this driver for example for flat database files (CSV).

The OGR provider requires a recent (3+) version of GDAL to be installed.

providers:
    - type: feature
      name: OGR
      data:
        source_type: ESRI Shapefile
        source: tests/data/dutch_addresses_shape_4326/inspireadressen.shp
        source_options:
          ADJUST_GEOM_TYPE: FIRST_SHAPE
        gdal_ogr_options:
          SHPT: POINT
      id_field: fid
      layer: inspireadressen
providers:
    - type: feature
      name: OGR
      data:
        source_type: WFS
        source: WFS:https://geodata.nationaalgeoregister.nl/rdinfo/wfs?
        source_options:
            VERSION: 2.0.0
            OGR_WFS_PAGING_ALLOWED: YES
            OGR_WFS_LOAD_MULTIPLE_LAYER_DEFN: NO
         gdal_ogr_options:
            GDAL_CACHEMAX: 64
            GDAL_HTTP_PROXY: (optional proxy)
            GDAL_PROXY_AUTH: (optional auth for remote WFS)
            CPL_DEBUG: NO
      id_field: gml_id
      layer: rdinfo:stations

MongoDB

Todo

add overview and requirements

providers:
    - type: feature
      name: MongoDB
      data: mongodb://localhost:27017/testdb
      collection: testplaces

PostgreSQL

Todo

add overview and requirements

providers:
    - type: feature
      name: PostgreSQL
      data:
          host: 127.0.0.1
          dbname: test
          user: postgres
          password: postgres
          search_path: [osm, public]
      id_field: osm_id
      table: hotosm_bdi_waterways
      geom_field: foo_geom

SQLiteGPKG

Todo

add overview and requirements

SQLite file:

providers:
    - type: feature
      name: SQLiteGPKG
      data: ./tests/data/ne_110m_admin_0_countries.sqlite
      id_field: ogc_fid
      table: ne_110m_admin_0_countries

GeoPackage file:

providers:
    - type: feature
      name: SQLiteGPKG
      data: ./tests/data/poi_portugal.gpkg
      id_field: osm_id
      table: poi_portugal

SensorThings API

The STA provider is capable of creating feature collections from OGC SensorThings API endpoints. Three of the STA entities are configurable: Things, Datastreams, and Observations. For a full description of the SensorThings entity model, see here. For each entity of Things, pygeoapi will expand all entities directly related to the Thing, including its associated Location, from which the geometry for the feature collection is derived. Similarly, Datastreams are expanded to include the associated Thing, Sensor and ObservedProperty.

The default id_field is @iot.id. The STA provider adds one required field, entity, and an optional field, intralink. The entity field refers to which STA entity to use for the feature collection. The intralink field controls how the provider is acted upon by other STA providers and is by default, False. If intralink is true for an adjacent STA provider collection within a pygeoapi instance, the expanded entity is instead represented by an intra-pygeoapi link to the other entity or it’s uri_field if declared.

providers:
    - type: feature
      name: SensorThings
      data: https://sensorthings-wq.brgm-rec.fr/FROST-Server/v1.0/
      uri_field: uri
      entity: Datastreams
      time_field: phenomenonTime
      intralink: true

If all three entities are configured, the STA provider will represent a complete STA endpoint as OGC-API feature collections. The Things features will include links to the associated features in the Datastreams feature collection, and the Observations features will include links to the associated features in the Datastreams feature collection. Examples with three entities configured are included in the docker examples for SensorThings.

Data access examples