Find Hot Spots (GeoAnalytics)


Given a set of features, identifies statistically significant hot spots and cold spots using the Getis-Ord Gi* statistic.

Learn more about how Hot Spot Analysis (Getis-Ord Gi*) works


Find Hot Spots


  • This tool identifies statistically significant spatial clusters of many features (hot spots) and few features (cold spots). It creates an output feature class with a z-score, p-value, and confidence level bin (Gi_Bin) for each feature in the input..

  • During analysis, the input points (incidents) are aggregated into bins of a specified size, and they are then analyzed to determine hot spots. The aggregated bins must contain a variety of values (counts of points in a bin should be highly variable).

  • The z-scores and p-values are measures of statistical significance that tell you whether to reject the null hypothesis using aggregated bins. That is, they indicate whether the observed spatial clustering of high or low values is more pronounced than one would expect in a random distribution of those values. The z-score and p-value fields do not reflect any kind of False Discovery Rate (FDR) correction.

  • A high z-score and small p-value for a feature indicates an intense presence of point incidents. A low negative z-score and small p-value indicates an absence of point incidents. The higher (or lower) the z-score, the more intense the clustering. A z-score near zero indicates no apparent spatial clustering.

  • The z-score is based on the randomization null hypothesis computation. For more information on z-scores, see What is a z-score? What is a p-value?

  • Find Hot Spots requires that the input layer is projected or that the output coordinate system is a projected coordinate system.

  • When input features are analyzed using time steps, each time step is analyzed independent of features outside of the time step.

  • The Time Step Reference parameter can be a date and time value or solely a date value; it cannot be solely a time value.

  • This geoprocessing tool is powered by ArcGIS GeoAnalytics Server. Analysis is completed on your GeoAnalytics Server, and results are stored in your content in ArcGIS Enterprise.

  • When running GeoAnalytics Server tools, the analysis is completed on the GeoAnalytics Server. For optimal performance, make data available to the GeoAnalytics Server through feature layers hosted on your ArcGIS Enterprise portal or through big data file shares. Data that is not local to your GeoAnalytics Server will be moved to your GeoAnalytics Server before analysis begins. This means that it will take longer to run a tool, and in some cases, moving the data from ArcGIS Pro to your GeoAnalytics Server may fail. The threshold for failure depends on your network speeds, as well as the size and complexity of the data. Therefore, it is recommended that you always share your data or create a big data file share.

    Learn more about sharing data to your portal

    Learn more about creating a big data file share through Server Manager

  • Similar analysis can also be completed using the following:


arcpy.geoanalytics.FindHotSpots(point_layer, output_name, {bin_size}, {neighborhood_size}, {time_step_interval}, {time_step_alignment}, {time_step_reference}, {data_store})
ParameterExplanationData Type

The point feature class for which hot spot analysis will be performed.

Feature Set

The name of the output layer with the z-score and p-value results.


The distance interval that represents the bin size and units into which the point_layer will be aggregated. The distance interval must be a linear unit.

Linear Unit

The spatial extent of the analysis neighborhood. This value determines which features are analyzed together to assess local clustering.

Linear Unit

The interval that will be used for the time step. This parameter is only used if time is enabled for point_layer.

Time Unit

Specifies how time steps will be aligned. This parameter is only available if the input points are time enabled and represent an instant in time.

  • END_TIMETime steps will align to the last time event and aggregate back in time.
  • START_TIMETime steps will align to the first time event and aggregate forward in time. This is the default.
  • REFERENCE_TIMETime steps will align to a specified date or time. If all points in the input features have a time stamp larger than the specified reference time (or it falls exactly on the start time of the input features), the time-step interval will begin with that reference time and aggregate forward in time (as occurs with the Start time alignment). If all points in the input features have a time stamp smaller than the specified reference time (or it falls exactly on the end time of the input features), the time-step interval will end with that reference time and aggregate backward in time (as occurs with the End time alignment). If the specified reference time is in the middle of the time extent of the data, a time-step interval will be created ending with the reference time provided (as occurs with the End time alignment); additional intervals will be created both before and after the reference time until the full time extent of the data is covered.

The time that will be used to align the time steps and time intervals. This parameter is only used if time is enabled for point_layer.


Specifies the ArcGIS Data Store where the output will be saved. The default is SPATIOTEMPORAL_DATA_STORE. All results stored in a spatiotemporal big data store will be stored in WGS84. Results stored in a relational data store will maintain their coordinate system.

  • SPATIOTEMPORAL_DATA_STOREOutput will be stored in a spatiotemporal big data store. This is the default.
  • RELATIONAL_DATA_STOREOutput will be stored in a relational data store.

Derived Output

NameExplanationData Type

The statistically significant hot spots.

Feature Set

Code sample

FindHotSpots (Python window)

The following Python window script demonstrates how to use the FindHotSpots tool.

# Name:
# Description: Find Hots Spots of 311 calls for bins of 500 meters looking at neighbors withing 1 kilometers. Complete the analysis for each month. 
# Requirements: ArcGIS GeoAnalytics Server

# Import system modules
import arcpy

# Set local variables
inFeatures = ""
bins = "500 Meters"
neighborhood = "1 Kilometers"
timeStep = "1 Months"
outFS = "HotSpotsOF311Data"

# Execute Find Hot Spots
arcpy.geoanalytics.FindHotSpots(inFeatures, outFS, bins, neighborhood, timeStep, 
                                None, None, dataStore)


Output Coordinate System

The coordinate system that will be used for analysis. Analysis will be completed in the input coordinate system unless specified by this parameter. For GeoAnalytics Tools, final results will be stored in the spatiotemporal data store in WGS84.

Licensing information

  • Basic: Requires ArcGIS GeoAnalytics Server
  • Standard: Requires ArcGIS GeoAnalytics Server
  • Advanced: Requires ArcGIS GeoAnalytics Server

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