A zone is defined as all areas in the input that have the same value. The areas do not have to be contiguous. Both raster and feature can be used for the zone input.
If the Input Raster or Feature Zone Data (in_zone_data in Python) value is a raster, it must be an integer raster.
If the Input Raster or Feature Zone Data is a feature, it will be converted to a raster internally using the cell size and cell alignment from the Input Value raster (in_value_raster in Python) parameter.
When the cell size of the Input Raster or Feature Zone Data and the Input Value Raster is different, the output cell size will be the Maximum Of Inputs value, and the Input Value Raster will be used as the snap raster internally. If the cell size is the same but the cells are not aligned, the Input Value Raster will be used as the snap raster internally. Either of these cases will trigger an internal resampling before the zonal operation is performed.
When the zone and value inputs are both rasters of the same cell size and the cells are aligned, they will be used directly in the tool and will not be resampled internally during tool processing.
If the Input Raster or Feature Zone Data is a feature, for any of the zone features that do not overlap any cell centers of the value raster, those zones will not be converted to the internal zone raster. As a result, those zones will not be represented in the output. You can manage this by determining an appropriate value for the cell size environment that will preserve the desired level of detail of the feature zones, and specify it in the analysis environment.
If the Input Raster or Feature Zone Data value is a point feature, more than one point may be contained in any particular cell of the value input raster. For such cells, the zone value is determined by the point with the lowest ObjectID field (for example, OID or FID).
If the Input Raster or Feature Zone Data value has overlapping polygons, the zonal analysis will not be performed for each individual polygon. Since the feature input is converted to a raster, each location can have only one value.
An alternative method is to process the zonal operation iteratively for each of the polygon zones and collate the results.
When specifying the Input Raster or Feature Zone Data value, the default zone field will be the first available integer or text field. If no other valid fields exist, the ObjectID field (for example, OID or FID) will be the default.
The supported statistics type depends on the data type of the Input Value Raster value, and the statistics calculation type specified by the Calculate Circular Statistics parameter.
If the data type is integer, arithmetic statistics calculation supports the Mean, Majority, Maximum, Median, Minimum, Minority, Percentile, Range, Standard deviation, Sum, and Variety options; circular statistics calculation supports the Mean, Majority, Minority, Standard deviation, and Variety options.
If the data type is float, arithmetic statistics calculation supports the Mean, Maximum, Median, Minimum, Percentile, Range, Standard deviation, and Sum options; circular statistics calculation supports the Mean and Standard deviation options.
For majority and minority calculations, when there is a tie, the output will be the lowest of the tied values.
To calculate circular statistics, check the Calculate Circular Statistics parameter (circular_calculation = "CIRCULAR" in Python), and specify a value for Circular Wrap Value (circular_wrap_value in Python).
Supported multidimensional raster dataset types include multidimensional raster layer, mosaic, image service, and Esri's CRF.
The data type (integer or float) of the output is dependent on the zonal calculation being performed and the input value raster type. See How the zonal statistics tools work for the specific behavior of a statistic.
By default, this tool will take advantage of multicore processors. The maximum number of cores that can be used is four.
To use fewer cores, use the Parallel Processing Factor environment setting.