Calculate Density
Calculate Density uses input point features to calculate a density map within an area of interest.
Examples
Bird counts can be used to calculate species densities. The densities can then be compared to land-cover data to determine which habitats each species prefers.
Use the Calculate Density capability
Calculate Density can be run on maps with point layers.
Use the following steps to run the Calculate Density analysis capability:
- If necessary, click the map card to activate it. A card is active when the toolbar and Action button
appear. - Click the Action button, then choose Calculate Density.
- For Choose a point layer, select the layer for which you want to calculate density.
- For Choose a field of totals, select a field to weight your density by, if necessary. See Usage notes for more information.
- Expand Additional options and enter values for the Search distance, Classify by, and Number of classes parameters, if necessary. See Usage notes for more information.
- Click Run.
Usage notes
The Choose a point layer parameter is used to select a dataset to calculate densities. Only point features are available in the drop-down menu.
The Choose a field of totals, if each point represents more than one event optional parameter is used if the points have a count other than 1. For example, if you have a dataset for retail locations that includes a field for revenue, you could use the revenue field in the Choose a field of totals parameter to create a density of sales amount, rather than locations. However, if you have a dataset with crime locations and you want to know which areas have the highest crime density, you would run Calculate Density using just the point locations.
The Additional options choice can be expanded to reveal the Search distance, Classify by, and Number of classes parameters. The following table summarizes these three parameters, including their default values:
Parameter | Description | Default value |
|---|---|---|
Search distance | A distance (in miles, feet, kilometers, or meters) that is used to find input features within the same neighborhood as the focal feature. | An appropriate search distance will be calculated using the locations of the input features. The units of the search distance will be based on the default units for your account. |
Classify by | The classification scheme used to display the resulting density layer. Options are Equal Interval, Equal Area, Geometric Interval, Natural Breaks, and Standard Deviation. | Equal Interval |
Number of classes | The number of classes to be used in the result layer. Used with the classification scheme in the Classify by parameter. | 10 |
Limitations
Densities can only be calculated for point features.
How Calculate Density works
Calculate Density applies a default search distance and classification scheme, which can be updated using the Additional options parameter. The following sections explain how the default search distance is calculated and describe the available classification schemes.
Search distances
The default search radius applies an algorithm to your data based on both the extent of your data and the density of the points. The Search distance field appears blank because the default radius is not calculated until the analysis begins. When you leave the Search distance field blank, the default radius is applied.
If you prefer to specify your own search radius, consider that the larger the search radius, the more generalized the pattern. A smaller search radius shows more local variation but may miss the broader picture.
Classification schemes
The following table summarizes the classification schemes used in the Classify by parameter:
Classification | Description |
|---|---|
Equal Interval | Areas are created such that the range of density values is equal for each area. |
Geometric Interval | Areas are based on class intervals that have a geometrical series. This method ensures that each class range has approximately the same number of values in each class and the change between intervals is consistent. |
Natural Breaks | Class intervals for areas are based on natural groupings of the data. Class break values are identified that best group similar values and maximize the differences between classes. |
Equal Area | Areas are created such that the size of each area is equal. For example, if the result layer has more high-density values than low-density values, more areas will be created for high densities. |
Standard Deviation | Areas are created based on the standard deviation of the predicted density values. |