The Calculate Density task creates a density layer from point features by spreading known quantities of some phenomenon (represented as attributes of the points) across the raster. The result is a layer of areas classified from least dense to most dense.
For point input, each point should represent the location of some event or incident, and the result layer represents a count of the incident per unit area. A higher density value in a new location means that there are more points near that location. In many cases, the result layer can be interpreted as a risk surface for future events. For example, if the input points represent locations of lightning strikes, the result layer can be interpreted as a risk surface for future lightning strikes.
Other use cases of this tool include the following:
- Creating crime density maps to help police departments properly allocate resources to high crime areas.
- Calculating densities of hospitals within a county. The result layer will show areas with high and low accessibility to hospitals, and this information can be used to decide where new hospitals should be built.
- Identifying areas that are at high risk of forest fires based on historical locations of forest fires.
- Locating communities that are far from major highways in order to plan where new roads should be constructed.
http://<raster analysis url>/CalculateDensity/submitJob
The following table lists the parameters with syntax and details for each.
The feature layer that the density will be calculated on.
It can be a point, line or polygon dataset.
Syntax: This parameter can be:
The output image service name that will be created.
Syntax: A JSON object describes the name of the output or the output raster.
You can specify the name, or you can create an empty service using Portal Admin Sharing API and use the return JSON object as input to this parameter.
Output name example:
Output raster examples:
Provide a field specifying the number of incidents at each location. If each point represents a single incident, do not provide a count field.
Domain: Integer or float field
Syntax: A string that represents a field name.
The size of the neighborhood within which to calculate the density. The radius size must be larger than the binSize.
For example, if you provide a search distance of 1800 meters, the density of any location in the output layer is calculated based on features that are within 1800 meters of the location. Any location that does not have any incidents within 1800 meters will receive a density value of zero.
If no distance is provided, a default will be calculated that is based on the locations of the input features and the values in the count field (if a count field is provided).
Domain: Meters, Kilometers, Feet, Miles
The desired output units of the density values.
The default is based on the units specified in your profile. If the units are set to Metric, the default is SQUARE_KILOMETERS. If your profile is set to US Standard, the default is SQUARE_MILES.
Possible area units are:
Specify the cell size to use for the output raster.
Domain: Meters, Kilometers, Feet, Miles
Default: Same as the analysis environment
Contains additional settings that affect task execution.
This task has the following settings:
The response format. The default response format is html.
Values: html | json
When you submit a request, the task assigns a unique job ID for the transaction.
"jobId": "<unique job identifier>",
"jobStatus": "<job status>"
After the initial request is submitted, you can use the jobId to periodically check the status of the job and messages as described in Checking job status. Once the job has successfully completed, you use the jobId to retrieve the results. To track the status, you can make a request of the following form:
http://<raster analysis url>/CalculateDensity/jobs/<jobId>
When the status of the job request is esriJobSucceeded, you can access the results of the analysis by making a request of the following form:
http://<raster analysis url>/jobs/<jobId>/results/outputRaster?token=<your token>&f=json
This is the density raster.
The result has properties for parameter name, data type, and value. The content of value is always the itemid of the output raster dataset and the image service URL. For example: