Spatial Analysis
Components to perform more advanced geospatial analytics leveraging the spatial properties and patterns in your data.
K-Nearest Neighbors
This component requires the CARTO Analytics Toolbox installed in the chosen connection to build the workflow.
Description
Finds the K nearest neighbors for each point in the input table based on geographic distance. Returns pairs of point IDs with their distances, useful for proximity analysis, network construction, and spatial clustering. Optionally filter results by maximum distance.
Inputs
Points table [Table]Id column [Column]Geo column [Column]Number of nearest neighbors [Number]Maximum distance: Defines the maximum distance where neighbors will be considered.
Outputs
Result table [Table]
External links
ST Cluster DBSCAN
Description
Groups spatial features into clusters using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm. Features within the search radius are grouped together if they have at least the minimum number of neighbors. Returns a 'cluster' column with cluster IDs (NULL for noise points that don't belong to any cluster).
Inputs
Source table [Table]Geo column [Column]Search radius (m) [Number]Minimum number of geographies [Number]
Outputs
Result table [Table]
External links
ST Cluster K-Means
This component requires the CARTO Analytics Toolbox installed in the chosen connection to build the workflow.
Description
Groups spatial features into K clusters using the K-Means algorithm based on geographic proximity. Divides the input points into the specified number of clusters, minimizing the distance from each point to its cluster centroid. Returns a 'cluster' column with cluster IDs (0 to K-1).
Inputs
Source table [Table]Geo column [Column]Number of clusters [Number]
Outputs
Result table [Table]
External links
ST Count Points in Polygons
Description
This component takes a points table and a polygons table. It creates a new table with the same content as the polygons table, with an additional column containing the number of points from the points table that fall within each polygon.
Inputs
Points table [Table]Polygons table [Table]Geo column in points table [Column]Geo column in polygons table [Column]Column with identifier in polygons table [Column]
Outputs
Result table [Table]
ST Delaunay Polygons
This component requires the CARTO Analytics Toolbox installed in the chosen connection to build the workflow.
Description
This component computes a Delaunay triangulation based in a input table with points.
It creates a new table with a 'geom' column containing the triangulation geographies (lines or polygons)
Inputs
Source table [Table]Geo column [Column]Return lines [Boolean]
Outputs
Result table [Table]
External links
ST Voronoi
This component requires the CARTO Analytics Toolbox installed in the chosen connection to build the workflow.
Description
This component computes a Voronoi tesellation based in a input table with points.
It creates a new table with a 'geom' column containing the triangulation geographies (lines or polygons).
The maximum number of points used to compute Voronoi diagrams is 300,000. This limit ensures efficient computation while maintaining accuracy in delineating regions based on proximity to specified points.
Inputs
Source table [Table]Geo column [Column]Return lines [Boolean]
Outputs
Result table [Table]
External links
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