Zonal Statistics
Definition
Zonal Statistics is a significant concept in the geographical information system (GIS) analysis which is mainly used to compute the values of a raster within the zones of another dataset. Zonal operations are actually spatial operation that is based on geographic features (zones) defined by certain datasets. These datasets may be either vector (polygon) or raster, but the output is always a raster dataset. The purpose of zonal statistics is to calculate and display statistical information about the characteristics of the zones of a certain raster dataset. By using this tool, users could extract the value of a variety of spatial information, like land use, population density, or physical attribute within predefined zones.
What is Zonal Statistics?
In GIS analysis, zonal statistics serves as a useful method for categorizing and summarizing different spatial data entities. It usually involves analyzing raster-based datasets as zones which might be defined by existing raster areas, vector polygon regions, or other specific criteria such as watersheds, land use type or forest covers.
Each zone of the raster dataset (like pixels or grid cells that share the same value) is defined by the input zone dataset and analyzed independently of every other zone in the chosen dataset. While performing zonal statistics, statistical parameters like mean, maximum, minimum, standard deviation, sum, and count of the pixels in each zone are usually calculated.
In addition to quantitative summary, zonal statistics also helps in enabling pattern identification, spatial distribution study, hotspots or cold spots finding within the geographic areas of interest. For example, it can be used to find out areas of high population density within a city or regions of high crop productivity in an agricultural field.
