Visual Point Clustering

The VisualPointClustering is a clustering operator for point collections that removes clutter and preserves the spatial structure of the input. The output is a point collection with a count and radius attribute. The operator utilizes the input resolution of the query to determine when points, being displayed as circles, would overlap. Moreover, it allows aggregating non-geo attributes to preserve the other columns of the input. For more information on the algorithm, cf. the paper Beilschmidt, C. et al.: A Linear-Time Algorithm for the Aggregation and Visualization of Big Spatial Point Data. SIGSPATIAL/GIS 2017: 73:1-73:4.

An exemplary use case for this operator is the visualization of point data in an online map application. There, you can use this operator as the final step of the workflow to cluster the points and display them as circles. These circles then pose a decluttered view of the data, e.g., via a WFS endpoint.

Errors

If the source value vector is not a point collection, an error is thrown.

If multiple columns in columnAggregates have the same names, an error is thrown.

Parameters

Name	Type	Description	Examples
minRadiusPx	number	Minimum circle radius in pixels.	8 10
deltaPx	number	Minimum circle-to-circle distance in pixels.	1
resolution	number	Spatial resolution used during clustering.	0.5 1
radiusColumn	string	Column name used to store the cluster radius.	"__radius"
countColumn	string	Column name used to store the number of clustered points.	"__count"
columnAggregates	object	Map of source columns to aggregation definitions used for clustered output attributes.	{"mean_population":{"columnName":"population","aggregateType":"MeanNumber","measurement":{"type":"unitless"}},"sample_names":{"columnName":"name","aggregateType":"StringSample"}}

Sources

Name	Type	Description
vector	VectorOperator	An operator that produces vector data.

Examples

{
    "type": "VisualPointClustering",
    "params": {
        "minRadiusPx": 8,
        "deltaPx": 1,
        "radiusColumn": "__radius",
        "countColumn": "__count",
        "columnAggregates": {
            "mean_population": {
                "columnName": "population",
                "aggregateType": "MeanNumber",
                "measurement": {
                    "type": "unitless"
                }
            },
            "sample_names": {
                "columnName": "name",
                "aggregateType": "StringSample"
            }
        }
    },
    "sources": {
        "vector": {
            "type": "OgrSource",
            "params": {
                "data": "places",
                "attributeProjection": ["name", "population"]
            }
        }
    }
}