Summarize center and dispersion

A center and dispersion analysis resulting in new layers that contain the center, mean, median, and ellipse of beetle infestations.

What is a center and dispersion analysis?

A center and dispersion analysis is the process of finding center features and directional distribution in feature data. It calculates the central, mean center, median center, or ellipse of features. To execute the analysis, use the spatial analysis service and the SummarizeCenterAndDispersion operation.

summarize center and dispersion

Real-world examples of this analysis include the following:

Finding the directional distribution of pest infestations.
Selecting the best place to open a library or other point of interest.
Finding the center of incidents of traffic crashes or crimes.

How to perform a center and dispersion analysis?

The general steps to performing summarize center and dispersion analysis are as follows:

Review the parameters for the SummarizeCenterAndDispersion operation.
Send a request to get the spatial analysis service URL.
Execute a job request with the following URL and parameters:
- URL: http://<YOUR_ANALYSIS_SERVICE>/arcgis/rest/services/tasks/GPServer/SummarizeCenterAndDispersion/submitJob
- Parameters:
  - analysisLayer: The point, line, or polygon features to be analyzed.
  - summarizeType: CentralFeature | MeanCenter | MedianCenter | Ellipse.
  - outputName: A string representing the name of the hosted feature layer to reutrn with the results.
Check the status.
Get the output layer results.
To see examples using ArcGIS API for Python, ArcGIS REST JS, and the ArcGIS REST API, go to Examples below.

URL Request

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http://<YOUR_ANALYSIS_SERVICE>/arcgis/rest/services/tasks/GPServer/SummarizeCenterAndDispersion/submitJob?<parameters>

Required parameters

Name	Description	Examples
`analysisLayer`	The point, line, or polygon features to be analyzed.	`{"url": <SERVICE_URL>}`
`token`	An OAuth 2.0 access token. Learn how to get an access token in Security and authentication.	`token=<ACCESS_TOKEN>`
`f`	The format of the data returned	`f=json` `f=pjson`

Key parameters

Name	Description	Examples
`summarizeType`	The method with which to summarize the `analysisLayer`.	`"summarizeType": ["CentralFeature","MeanCenter","MedianCenter","Ellipse"]`
`ellipseSize`	The size of the output ellipse in standard deviations. The default ellipse size is 1. Valid choices are 1, 2, or 3 standard deviations.	"ellipseSize": "3 standard deviations"
`weightField`	A numeric field in the `analysisLayer` to be used to weight locations according to their relative importance.
`outputName`	A string representing the name of the hosted feature layer to return with the results. NOTE: If you do not include this parameter, the results are returned as a feature collection (JSON).	`{"serviceProperties": {"name": "<SERVICE_NAME>"}}`

Example

Find the center of beetle infestation

This example uses the SummarizeCenterAndDispersion operation to find the mean and median points, as well as the directional distribution, of a douglas fir beetle infestation between the years 2020-2022.

The analysisLayer value is the Pest infestation hosted feature layer that is filtered by the type of beetle and the year. The summarizeType parameter is set to find the CentralFeature, MeanCenter, MedianCenter, and Ellipse. The analysis is weighted by the number of trees (NUM_TREES).

Summarize center and dispersion revealing statistical characteristics of forest infestation.

APIs

ArcGIS API for Python

ArcGIS REST JS

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analysisLayer = {
    "url": "https://services3.arcgis.com/GVgbJbqm8hXASVYi/arcgis/rest/services/PST_IF_PT_point/FeatureServer/0",
    "filter": "(PST_CMN_NM = 'Douglas-fir Beetle') AND (CPTR_YR >= 2020)",
}

results = summarize_center_and_dispersion(
    analysis_layer=analysisLayer,
    summarize_type=["CentralFeature", "MeanCenter", "MedianCenter", "Ellipse"],
    weight_field="NUM_TREES",
    ellipse_size="1 standard deviation",
    output_name="Summarize dispersion results", #Outputs results as a hosted feature layer.
    context={
        "overwrite": True,
        "extent": {
            "xmin": -15034729.266472297,
            "ymin": 5716733.479048933,
            "xmax": -12070195.56146081,
            "ymax": 7808050.572930799,
            "spatialReference": {"wkid": 102100, "latestWkid": 3857},
        },
    },
)

result_features = results["ellipse_result_layer"].query()

print(
    f"summarize result layer contains {len(result_features.features)} records"
)

Expand

Go to tutorial

Service requests

Request

HTTPHTTPcURL
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POST arcgis.com/sharing/rest/portals/self HTTP/1.1
Content-Type: application/x-www-form-urlencoded

&f=json
&token=<ACCESS_TOKEN>
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Response (JSON)

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{
  "helperServices": {
    // Other parameters
    "analysis": {
      "url": "https://<YOUR_ANALYSIS_SERVICE>/arcgis/rest/services/tasks/GPServer"
    },
    "geoenrichment": {
      "url": "https://geoenrich.arcgis.com/arcgis/rest/services/World/GeoenrichmentServer"
    }
  }
}

Request

HTTP

cURL

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POST <YOUR_ANALYSIS_SERVICE>/arcgis/rest/services/tasks/GPServer/SummarizeCenterAndDispersion/submitJob HTTP/1.1
Content-Type: application/x-www-form-urlencoded

token=<ACCESS_TOKEN>
&f=json
&analysisLayer={"url":"https://services3.arcgis.com/GVgbJbqm8hXASVYi/arcgis/rest/services/PST_IF_PT_point/FeatureServer/0","filter":"(PST_CMN_NM = 'Douglas-fir Beetle') AND (CPTR_YR >= 2020)"}
&summarizeType=["CentralFeature","MeanCenter","MedianCenter","Ellipse"]
&weightField=NUM_TREES
&ellipseSize=1 standard deviation
&context={"extent":{"xmin":-15034729.266472297,"ymin":5716733.479048933,"xmax":-12070195.56146081,"ymax":7808050.572930799,"spatialReference":{"wkid":102100,"latestWkid":3857}}}&outputName={"serviceProperties":{"name":"SumCenterDispersion_Result_PM"}}
&outputName={"serviceProperties":{"name":"Summarize dispersion results"}}

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Response (JSON)

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{
  "jobId": "<JOB_ID>",
  "jobStatus": "esriJobSubmitted",
  "results": {},
  "inputs": {},
  "messages": []
}

Request

HTTP

cURL

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POST <YOUR_ANALYSIS_SERVICE>/arcgis/rest/services/tasks/GPServer/SummarizeCenterAndDispersion/jobs/<JOB_ID> HTTP/1.1
Content-Type: application/x-www-form-urlencoded

f=json
&token=<ACCESS_TOKEN>

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Response (JSON)

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{
  "jobId": "<JOB_ID>",
  "jobStatus": "esriJobSucceeded",
  "results": {
    "centralFeatureResultLayer": {
      "paramUrl": "results/centralFeatureResultLayer"
    },
    "meanCenterResultLayer": {
      "paramUrl": "results/meanCenterResultLayer"
    },
    "medianCenterResultLayer": {
      "paramUrl": "results/medianCenterResultLayer"
    },
    "ellipseResultLayer": {
      "paramUrl": "results/ellipseResultLayer"
    }
  },
  "inputs": {},
  "messages": []
}

Request

HTTP

cURL

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POST <YOUR_ANALYSIS_SERVICE>/arcgis/rest/services/tasks/GPServer/SummarizeCenterAndDispersion/jobs/<JOB_ID>/results/ellipseResultLayer HTTP/1.1
Content-Type: application/x-www-form-urlencoded

f=json
&token=<ACCESS_TOKEN>

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Response (JSON)

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{
  "paramName": "ellipseResultLayer",
  "dataType": "GPString",
  "value": {
    "url": "https://services3.arcgis.com/GVgbJbqm8hXASVYi/arcgis/rest/services/SumCenterDispersion_Result_PM/FeatureServer/3",
    "itemId": "9dacd976ec4644f5988e0b922d6bcb5b"
  }
}

Tutorials

Learn how to perform related analyses interactively with Map Viewer and programmatically with ArcGIS API for Python, ArcGIS REST JS, and ArcGIS REST API.

Summarize data

Aggregate and summarize features using summarize analysis operations.

Services

Spatial analysis service

Process spatial datasets to discover relationships and patterns.

API support

	Aggregate points	Summarize center and dispersion	Summarize nearby	Summarize within
ArcGIS Maps SDK for JavaScript	¹	¹	¹	¹
ArcGIS Maps SDK for .NET
ArcGIS Maps SDK for Kotlin
ArcGIS Maps SDK for Swift
ArcGIS Maps SDK for Java
ArcGIS Maps SDK for Qt
ArcGIS API for Python
ArcGIS REST JS	¹	¹	¹	¹
Esri Leaflet	²	²	²	²
MapBox GL JS	²	²	²	²
OpenLayers	²	²	²	²

Full supportPartial supportNo support

1. Access with geoprocessing task
2. Access via ArcGIS REST JS

Tools

Map Viewer

Create, explore, and share web maps for 2D applications.

ArcGIS Pro

Explore, visualize, and analyze both 2D and 3D data with desktop GIS tools.

Mapping APIs and location services

Summarize center and dispersion

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