Interpolate points

An interpolation analysis resulting in a new layer with predicted elevation values from point features in Oregon.

What is an interpolation analysis?

An interpolation analysis is the process of estimating and predicting the location of new features and attribute values by using point features with numeric fields. To execute the analysis, use the spatial analysis service and the InterpolatePoints.

Real-world examples of this analysis include the following:

Interpolating air quality, soil nutrients, and rainfall levels.
Predicting heavy metal concentrations.
Predicting earthquake magnitudes.

How to perform an interpolation analysis

The general steps to performing an interpolation analysis are as follows:

Review the parameters for the InterpolatePoints operation.
Send a request to get the spatial analysis service URL.
Execute a job request with the following URL and parameters:
- URL: https://<YOUR_ANALYSIS_SERVICE>/arcgis/rest/services/tasks/GPServer/InterpolatePoints/submitJob
- Parameters:
  - inputLayer: Your points dataset as a hosted feature layer or feature collection.
  - field: The numeric field containing the values to interpolate.
  - outputName: A string representing the name of the hosted feature layer to return 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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https://analysis3.arcgis.com/arcgis/rest/services/tasks/GPServer/CalculateDensity/submitJob?<parameters>

Required parameters

Name	Description	Examples
`f`	The format of the data returned.	`f=json` `f=pjson`
`token`	An access token (API key or OAuth 2.0) with the required Spatial Analysis > Feature analysis privilege.	`token=<ACCESS_TOKEN>`
`inputLayer`	The point feature collection or hosted feature layer.	`{url:"https://services3.arcgis.com/GVgbJbqm8hXASVYi/arcgis/rest/services/Average_temperature_Oregon/FeatureServer/0"}`
`field`	The numeric field containing the values to interpolate.	`Elevation`

Key parameters

Name	Description	Examples
`interpolateOption`	A value declaring the preference for speed versus accuracy. The default is `5`.	`1`, `5`, `9`
`classificationType`	Determines how the predicted values will be classified into areas. The default is `GeometricInterval`.	`EqualArea`, `EqualInterval`, `GeometricInterval`, `Manual`
`classBreaks`	If the `classificationType` is `Manual`, then provide the class break values as a list.	`[1,3,5]`
`boundingPolygonLayer`	The layer specifying the polygons in which you want values to be interpolated.	`{url:"https://services3.arcgis.com/GVgbJbqm8hXASVYi/arcgis/rest/services/Delaware_County_Municipal_Boundaries/FeatureServer/0"}`
`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>"}}`
`context`	A bounding box or output spatial reference for the analysis.	`"extent":{"xmin:", "ymin:", "xmax:", "ymax:"}`

Code examples

Predict air quality

This example uses the InterpolatePoints operation to predict the air quality index (AQI) based on particle values that are 10 micrometers or smaller.

In the analysis, the inputLayer value is the AQI PM10 hosted feature layer. The DAILY_AQI_LEVEL is the field used to interpolate values.

Interpolation analysis showing the air quality indices for California.

APIs

ArcGIS API for Python

ArcGIS REST JS

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inputLayer = "https://services3.arcgis.com/GVgbJbqm8hXASVYi/arcgis/rest/services/aqi_pm10/FeatureServer/0"
aoiLayer = "https://services3.arcgis.com/GVgbJbqm8hXASVYi/arcgis/rest/services/California_State_Boundary/FeatureServer/0"

results = interpolate_points(
    input_layer=inputLayer,
    field="DAILY_AQI_VALUE",
    interpolate_option=5,
    classification_type="GeometricInterval",
    num_classes=10,
    bounding_polygon_layer=aoiLayer,
    output_prediction_error=False,
    #Outputs results as a hosted feature layer.
    output_name="Interpolate points result",
)

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

print(
    f"The interpolate points layer has {len(result_features.features)} new records"
)

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Service requests

Request

HTTP

cURL

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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>
Run in Postman

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/InterpolatePoints/submitJob HTTP/1.1
Content-Type: application/x-www-form-urlencoded

&f=json
&token=<ACCESS_TOKEN>
&inputLayer={"url":"https://services3.arcgis.com/GVgbJbqm8hXASVYi/arcgis/rest/services/aqi_pm10/FeatureServer/0"}
&field=DAILY_AQI_VALUE
&interpolateOption=5
&classificationType=GeometricInterval
&numClasses=10'\
&boundingPolygonLayer={{"url":"https://services3.arcgis.com/GVgbJbqm8hXASVYi/arcgis/rest/services/California_State_Boundary/FeatureServer/0"}}'
&outputPredictionError=false
&returnFeatureCollection=false
&outputName={"serviceProperties":{"name":"Interpolate points results"}}
&context={}
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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/InterpolatePoints/jobs/<JOB_ID> HTTP/1.1
Content-Type: application/x-www-form-urlencoded

&f=json
&token=<ACCESS_TOKEN>
Run in Postman

Response (JSON)

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// Executing job
{
  "jobId": "<JOB_ID>",
  "jobStatus": "esriJobExecuting",
  "results": {},
  "inputs": {},
  "messages": []
}
// Job succeeded
{
  "jobId": "<JOB_ID>",
  "jobStatus": "esriJobSucceeded",
  "results": {
      "pointClustersResultLayer": {
          "paramUrl": "results/resultLayer"
      },
  },
  "inputs": {},
  "messages": []
}

Request

HTTP

cURL

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

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

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{
  "paramName": "resultLayer",
  "dataType": "GPString",
  "value": {
      "url": "<SERVICE_URL>",
      "itemId": "<ITEM_ID>"
  }
}

Predict fuel prices

This example uses the InterpolatePoints operation to predict fuel prices in Madrid.

In the analysis, the inputLayer value is the Gasolineras hosted feature layer and the Precio_gas is the field used to interpolate values.

Interpolation analysis showing fuel prices (95) for Madrid and surrounding areas.

APIs

ArcGIS API for Python

ArcGIS REST JS

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results = interpolate_points(
    input_layer="https://services3.arcgis.com/GVgbJbqm8hXASVYi/arcgis/rest/services/Gasolineras/FeatureServer/0",
    field="Precio_gas",
    interpolate_option=5,
    classification_type="GeometricInterval",
    num_classes=10,
    #Outputs results as a hosted feature layer.
    output_name="Interpolate points results",
    context={
        "extent": {
            "xmin": -438873.975499999,
            "ymin": 4903874.0387,
            "xmax": -375084.7903,
            "ymax": 4945862.018,
            "spatialReference": {"wkid": 102100},
        },
    },
)

print(f"New item created : {results.itemid}")

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Service requests

Request

HTTP

cURL

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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>
Run in Postman

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/InterpolatePoints/submitJob HTTP/1.1
Content-Type: application/x-www-form-urlencoded

&f=json
&token=<ACCESS_TOKEN>
&inputLayer={"url":"https://services3.arcgis.com/GVgbJbqm8hXASVYi/arcgis/rest/services/Gasolineras/FeatureServer/0"}
&field=Precio_gas
&interpolateOption=5
&classificationType=GeometricInterval
&numClasses=10'
&outputPredictionError=false
&returnFeatureCollection=false
&outputName={"serviceProperties":{"name":"Interpolate points results"}}
&context={"extent":{"xmin":-439205.7832022423,"ymin":4903730.811446736,"xmax":-375075.11647106585,"ymax":4945924.051060095,"spatialReference":{"wkid":102100,"latestWkid":3857}}}
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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/InterpolatePoints/jobs/<JOB_ID> HTTP/1.1
Content-Type: application/x-www-form-urlencoded

&f=json
&token=<ACCESS_TOKEN>
Run in Postman

Response (JSON)

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// Executing job
{
  "jobId": "<JOB_ID>",
  "jobStatus": "esriJobExecuting",
  "results": {},
  "inputs": {},
  "messages": []
}
// Job succeeded
{
  "jobId": "<JOB_ID>",
  "jobStatus": "esriJobSucceeded",
  "results": {
      "pointClustersResultLayer": {
          "paramUrl": "results/resultLayer"
      },
  },
  "inputs": {},
  "messages": []
}

Request

HTTP

cURL

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

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

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{
  "paramName": "resultLayer",
  "dataType": "GPString",
  "value": {
      "url": "<SERVICE_URL>",
      "itemId": "<ITEM_ID>"
  }
}