Understanding point clustering
Coverage and concentration
A cluster map groups nearby point features into one symbol and displays how many rendered points it represents. Clustering reduces overlap without changing or aggregating the source records.
Cluster membership is based on screen distance, so groups separate and recombine as the map zoom changes. Lines and polygons are not included in point clusters.
How to interpret the pattern
Use cluster counts to navigate dense data, not as fixed geographic totals. Zoom in or select an individual point before interpreting its properties.
Two maps must use the same zoom and cluster settings before their cluster patterns can be compared visually.