Point clusters with DBSCAN

geo_dbscan() finds clusters of points with DBSCAN (Ester et al. 1996), the clustering tool of the GeoSpaX plug-ins: points with at least min_pts neighbours within eps form cluster cores, points near a core join its cluster, and the rest are noise. Distances are in metres for geographic data (points are projected to an equal-area projection centred on them), so eps means the same thing anywhere on Earth. The search uses a grid index in C++. Each cluster also gets its outline as a convex hull.

Usage

geo_dbscan(data, eps, min_pts = 5, lon = lon, lat = lat, crs = 4326)

Arguments

data

An sf point table, or a data frame with coordinate columns.

eps

Neighbourhood radius, in metres (or in the units of a projected CRS).

min_pts

Smallest number of points within eps (the point itself included) for a core point.

lon, lat

<data-masking> Coordinate columns when data is not sf.

crs

Coordinate reference system of lon/lat (default WGS 84).

Value

The points as sf with cluster (integer; 0 for noise) and core (logical). Attribute "hulls" holds an sf table of cluster outlines with the number of points in each.

References

Ester M, Kriegel H-P, Sander J, Xu X (1996) A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of KDD-96: 226-231.

See also

geo_hotspot() for hot spots of values, geo_landscape() for fragmentation.

Examples

# Earthquakes near Fiji since 1964 (datasets::quakes)
cl <- geo_dbscan(datasets::quakes, eps = 50000, min_pts = 15,
  lon = long, lat = lat)
table(cl$cluster)
#> 
#>   0   1   2   3   4   5   6   7   8   9 
#> 513 259  23  25  76  19  26  17  27  15 
attr(cl, "hulls")
#> Simple feature collection with 9 features and 2 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -179.98 ymin: -28.1 xmax: 179.69 ymax: -10.96
#> Geodetic CRS:  WGS 84
#>   cluster   n                       geometry
#> 1       1 259 POLYGON ((-179.36 -22.64, -...
#> 2       2  23 POLYGON ((-175.94 -20.31, -...
#> 3       3  25 POLYGON ((165.76 -12.08, 16...
#> 4       4  76 POLYGON ((-179.98 -25.59, 1...
#> 5       5  19 POLYGON ((-174.68 -16.1, -1...
#> 6       6  26 POLYGON ((169.5 -19.64, 169...
#> 7       7  17 POLYGON ((-173.2 -15.66, -1...
#> 8       8  27 POLYGON ((-177.75 -28.1, -1...
#> 9       9  15 POLYGON ((-175.36 -23.95, -...