Often, once a land cover classification or some other process (e.g. NDVI) is performed, the output raster provides the visual representation of the result, but analysts sometimes need to know what the area of land cover types or the “healthy vegetation” area is in the image.
ArcGIS Pro’s Zonal Statistics as Table can be used to generate a number of image statistics based on pixel counts within “zones” (e.g. specific land cover types or “continuous” data that has been “remapped” to integer values) can then be used as the “zones” in the Zonal Statistics as Table routine. The result of Zonal Statistics as table is a stand alone table with columns such as pixel counts, “Area,” minimum, maximum, mean, standard deviation, variance, etc for the different zones (and for land cover classification results, the “class name” and the class “number” both originating from the classification scheme developed during the image classification process.
Once the Zonal Statistics table is computed, an extra field can be added (e.g. Acres, Hectares) and use the Calculate Field routine to compute a unit conversion that is more meaningful.
The first 2 videos below show how the NDVI result can be “remapped” using the Raster Function Remap the floating point NDVI values into a small number of “integer” values. This remapped result is then “exported” (Data–Export Raster) so that the output from the Remap routine can contain unsigned 8-bit data values. The exported result is then used as the input to the Zonal Statistics as Table routine to generate the “metrics” for the NDVI “integer” groups (zones). In this example, 3 groupings are used (1 – no vegetation, 2- sparse vegetation, 3-significant vegetation). The groupings are based on the general comments made by the USGS.
The third video shows how to use the Zonal Statistics as Table routine on a classified land cover data set. The land cover classification image does not need to be “remapped” since the data is already stored as unsigned 8-bit data.
The data and write up provided reference larger images than in the PPKX file. The write up is to provide the step to perform the processes. Analysts using the data provided will experience different output values and geographic extents from the documented steps. The data has been subset to create a smaller PPKX file.
Computing Areas using Zonal Statistics as Table
Raster Zonal Stats PPKX file (zip file)
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