The Find Point Clusters tool finds clusters of point features within surrounding noise based on their spatial distribution.
A Non-Governmental Organization is studying a particular pest-borne disease and has a point dataset representing households in a study area, some of which are infested, some of which are not. By using the Find Point Clusters tool, an analyst can determine the largest clusters of infested households to help pinpoint an area to begin treatment and extermination of pests.
The input for Find Point Clusters is a single point layer.
The Minimum number of points to be considered a cluster parameter determines the minimum number of points that must be found within proximity of each other to be considered a cluster. If fewer points are found within the range, the points will be dedicated as noise.
The Limit the search range to parameter sets a limit to the search range. Any points found outside the limit will be dedicated as noise.
Click Show Credits before you run your analysis to check how many credits will be consumed.
Use Find Point Clusters to find clusters of point features within surrounding noise based on their spatial distribution. Other tools that may be useful are the following:
Map Viewer analysis tools
If you are interested in determining if there is any statistically significant clustering in the spatial pattern of your data, use the Find Hot Spots tool.
If you are interested in creating a density map of your point or line features, use the Calculate Density tool.
If you are interested in determining if there are any statistically significant outliers in the spatial pattern of your data, use the Find Outliers tool.
ArcGIS Desktop analysis tools
Find Point Clusters performs the function of the Density-based Clustering tool.