Publishing raster data to OGC API - Coverages

OGC API - Coverages provides geospatial data access functionality to raster data.

To add raster 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	subset	bbox	datetime
Rasterio	✅	✅	✅	✅
Xarray	✅	✅	✅	✅

Below are specific connection examples based on supported providers.

Connection examples

Rasterio

Note

Requires Python package Rasterio

The Rasterio provider plugin reads and extracts any data that Rasterio is capable of handling.

providers:
    - type: coverage
      name: rasterio
      data: tests/data/CMC_glb_TMP_TGL_2_latlon.15x.15_2020081000_P000.grib2
      options:  # optional creation options
          DATA_ENCODING: COMPLEX_PACKING
      format:
          name: GRIB
          mimetype: application/x-grib2

Note

The Rasterio provider format.name directive requires a valid GDAL raster driver short name.

xarray

Note

Requires Python package Xarray

The Xarray provider plugin reads and extracts NetCDF and Zarr data.

providers:
    - type: coverage
      name: xarray
      data: tests/data/coads_sst.nc
      # optionally specify x/y/time fields, else provider will attempt
      # to derive automagically
      x_field: lon
      y_field: lat
      time_field: time
      # optionally specify the coordinate reference system of your dataset
      # else pygeoapi assumes it is WGS84 (EPSG:4326).
      storage_crs: 4326
      format:
         name: netcdf
         mimetype: application/x-netcdf

providers:
    - type: coverage
      name: xarray
      data: tests/data/analysed_sst.zarr
      format:
         name: zarr
         mimetype: application/zip

Note

Zarr files are directories with files and subdirectories. Therefore a zip file is returned upon request for said format.

Note

When referencing NetCDF or Zarr data stored in an S3 bucket, be sure to provide the full S3 URL. Any parameters required to open the dataset using fsspec can be added to the config file under options and s3.

Note

When providing a storage_crs value in the xarray configuration, specify the coordinate reference system using any valid input for pyproj.CRS.from_user_input.

Data access examples

• list all collections

  • http://localhost:5000/collections

• overview of dataset

  • http://localhost:5000/collections/foo

• schema of dataset

  • http://localhost:5000/collections/foo/schema

• coverage access via CoverageJSON (default)

  • http://localhost:5000/collections/foo/coverage?f=json

• coverage access via native format (as defined in provider.format.name)

  • http://localhost:5000/collections/foo/coverage?f=GRIB

• coverage access with comma-separated properties

  • http://localhost:5000/collections/foo/coverage?properties=1,3

• coverage access with subsetting

  • http://localhost:5000/collections/foo/coverage?subset=lat(10:20)&subset=long(10:20)

• coverage with bbox

  • http://localhost:5000/collections/foo/coverage?bbox=10,10,20,20

• coverage with bbox and bbox CRS

  • http://localhost:5000/collections/foo/coverage?bbox=-8794239.772668611,5311971.846945471,-8348961.809495518,5621521.486192066&bbox=crs=3857

Note

.../coverage queries which return an alternative representation to CoverageJSON (which prompt a download) will have the response filename matching the collection name and appropriate file extension (e.g. my-dataset.nc)