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Overview

The GIS Service provides dedicated storage service for spatial data in the vector data model. In the vector data model, objects from the real world can be represented as features in collections called feature classes. Features are objects with geometry and some properties (also called attributes). A Feature Class can contain features of the same geometry type and with same set of attributes. All features in a feature class are in the same coordinate system.

Dataset types stored in the GIS service are: gisvector.

Data must be imported using the conventional transfer pipeline. Supported input formats include ESRI Shapefile, GeoJson file, or DHI XYZ format. After a successful upload, the GIS service allows manipulations on the feature class.

Get a specific dataset with all features using GET​/api​/gis​/dataset​/{id}, get only the feature class extent by GET​/api​/gis​/dataset​/{id}​/extent.

Add and remove attribute by PATCH​/api​/gis​/dataset​/{id}​/add-attribute and PATCH​/api​/gis​/dataset​/{id}​/delete-attribute, respectively.

Add, delete, or update features to, from, and in a specific dataset by PATCH​/api​/gis​/dataset​/{id}​/add-features, PATCH​/api​/gis​/dataset​/{id}​/delete-features, and PATCH​/api​/gis​/dataset​/{id}​/update-features respectively.

Or to run a query so a subset of features from a feature class is returned by POST​/api​/gis​/dataset​/{id}​/query

It is also possible to manipulate individual features. Add a new feature by POST​/api​/gis​/dataset​/{id}​/feature, get a single feature by GET​/api​/gis​/dataset​/{id}​/feature​/{featureId}, remove one by DELETE​/api​/gis​/dataset​/{id}​/feature​/{featureId}, or update a feature geometry or attributes by PUT​/api​/gis​/dataset​/{id}​/feature. Or just update attributes of a specific feature by PATCH​/api​/gis​/dataset​/{id}​/feature​/{featureId}

Limitations

  • The GIS service provides only storage for data in vector data model, so objects that can be represented by points, lines, and polygons and a set of attributes.
  • Standalone attribute tables and relationships between features are not supported.
  • Endpoints for querying features and getting all features from a feature class do not include any paging. Therefore, requests to these endpoints are likely to time out for large feature classes if no query parameters are specified.