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Merge pull request #131 from NASA-IMPACT/wmts-integration
Add docs on API integration
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services/apis.qmd

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@@ -11,7 +11,6 @@ Most of the VEDA APIs are hosted out of a single project ([veda-backend](https:/
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While some of our services are already very mature, VEDA is currently in the build-up phase. Therefore, we do not yet have a production environment for users.
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Maintenance on the staging environment will be announced internally and selected known stakeholders will be informed of any larger changes.
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### Production (stable): Coming soon
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### Staging (maintenance will be announced):
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* List collections: [https://dev.openveda.cloud/api/stac/collections](https://dev.openveda.cloud/api/stac/collections)
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* Raster API (tiling): [https://dev.openveda.cloud/api/raster/docs](https://dev.openveda.cloud/api/raster/docs)
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* STAC viewer (experimental): [https://dev.openveda.cloud/api/stac/index.html](https://dev.openveda.cloud/api/stac/index.html)
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## Using tile layers in external services
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### UI for single tile layers
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As you can see from our API docs referenced above, our raster API provides [WMTS](https://www.ogc.org/standard/wmts/) and XYZ tiles for public consumption.
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For any layer you are seeing in the VEDA dataset Explorer, you can retrieve the tile URL:
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![VEDA Dashboard Exploration API grab](api-integration-wmts-xyz-from-exploration.png)
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And paste that into any client that loads these tiles, like QGIS, ArcGIS, Leaflet, even online tools such as [geojson.io](https://geojson.io) or [felt.com](https://felt.com).
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### STAC for layer timeseries
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If you want to integrate tile layer time series into your application, you will need to fetch the information about
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which time steps exist and what the layer URLs are from our Spatio Tempoeral Asset Catalog (STAC) API (see above).
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That is because, unfortunately, neither XYZ nor WMTS have time series capabilities (unlike good old [WMS](https://www.ogc.org/standard/wms/), which our services do not provide, though).
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You can see how to retrieve time steps and tile layer URLs from these tutorial Python notebooks (mostly REST API calls):
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1. [Using /stac/tilejson.json with STAC collection and item IDs](../notebooks/datasets/ocean-npp-timeseries-analysis.qmd#visualizing-the-raster-imagery)
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2. [Creating layers from filters and mosaics (advanced)](../notebooks/quickstarts/hls-visualization.qmd)
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It comes down to querying for STAC items (timesteps) and then asking the Raster API for `tilejson.json` specifications for the items you are interested in.
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Once you retrieved the WMTS or XYZ layer URLs this way, you can use them seamlessly with all mapping clients.

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