pygeoapi, as so many other applications is configured through a YAML file. Although YAML is a human-readable data serialization language, maybe data serialization languages are not for all palates. The pygeoapi config QGIS plugin was develop with the motivation of lowering the barrier to configuring pygeoapi, and in this way making the publication of data as OGC API more accessible to everyone.
First and foremost, the plugin lets you read and write a pygeoapi configuration file in a user friendly environment, which is known by most GIS users: QGIS. It also supports reading and writing a configuration from a running pygeoapi instance, through the pygeoapi admin API.
Currently the plugin has many limitations, and you can read about them in the documentation. But it is an open source project, and we are excited to receive contributions from the community, in the form of new features or bug fixes, directly in the project repository.
The video bellow, demonstrates how-to pull and push a configuration from a running pygeoapi instance, using the pygeoapi configurator. We hope this can entice your appetite for trying out the plugin, and most importantly, we hope the plugin can be useful for your workflows. Enjoy it!
Vector tiles have been around for a while and they seem to combine the best of both worlds. They provide design flexibility, something we usually associate to vector data, while enabling fast delivery, like we generally see on raster services. The mvt specification, based on Google’s protobuf format, packages geographic data into pre-defined roughly-square shaped “tiles” for transfer over the web.
The OGC API – Tiles standard, enables sharing vector tiles while ensuring interoperability among services. It is a very simple format, which formalizes what most applications are already doing in terms of tiling, while adding some interesting (optional) features. You can find more information on: tiles.developer.ogc.org .
You can check some OGC API – Tiles collections in the eMOTIONAL Cities catalogue. On this map, we show the results of urban health outcomes (Prevalence rates of cardiovascular diseases) in 350m hexagonal grids of Inner London. It is rendered according to the mean value.
On the developer console, we can inspect how the attribute values of the vector tiles are exposed to the client.
Another option for interactive maps that require access to attributes, would be to retrieve a GeoJSON from an OGC API – Features endpoint. In that case, the client would need to load all the features at the start, and then carry these features in memory. If we have a high number of features, or many different layers, this could result in a less responsive application.
As an experiment, we loaded a web application with a base layer and two collections with 3480 and 3517 features (“hex350_grid_cardio_1920” and “hex350_grid_pm10_2019”). When the collections were loaded as vector tiles, the application took 20 milliseconds to load. On the other hand, when the collections were loaded as features it took 6887 milliseconds.
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