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) is a raster, it must be an integer raster.
If the Input raster or feature zone data (in_zone_data in Python) 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).
When the cell size of the Input raster or feature zone data (in_zone_data in Python) and the Input value raster (in_value_raster in Python) 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 execution.
If the Input raster or feature zone data (in_zone_data in Python) 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 (in_zone_data in Python) is a point feature, it is possible to have more than one point contained within 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 (in_zone_data in Python) 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 (in_zone_data in Python), 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 Input value raster (in_value_raster in Python) can be either integer or floating point. However, when it is floating-point type, the options for calculating majority, minority, and variety will not be available.
For majority and minority calculations, when there is a tie, the output for the zone is based on the lowest of the tied values. See How the zonal statistics tools work for more information.
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.
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 parallelProcessingFactor environment setting.
See Analysis environments and Spatial Analyst for additional details on the geoprocessing environments that apply to this tool.
