This tool can be used to extract common descriptive statistics associated with the distribution of some underlying data raster based on feature units defined by a feature definition raster. For example, this tool can be used to measure the maximum or average slope gradient (data image) for each of a group of watersheds (feature definitions). Although the data raster can contain any type of data, the feature definition raster must be categorical, i.e. it must define area entities using integer values.
The stat
parameter can take the values, 'mean', 'median', 'minimum', 'maximum', 'range', 'standard deviation', or 'total'.
If an output image name is specified, the tool will assign the descriptive statistic value to each of the spatial entities defined in the feature definition raster. If text output is selected, an HTML table will be output, which can then be readily copied into a spreadsheet program for further analysis. This is a very powerful and useful tool for creating numerical summary data from spatial data which can then be interrogated using statistical analyses. At least one output type (image or text) must be specified for the tool to operate.
NoData values in either of the two input images are ignored during the calculation of the descriptive statistic.
def zonal_statistics(self, data_raster: Raster, feature_definitions_raster: Raster, stat_type: str = "mean") -> Tuple[Raster, str]: ...