Using Cell, Neighborhood, and Zonal Statistics
You need statistics to
describe your data, to add validity to your research, and to make sound
decisions. Traditionally, statistics are used on a random but representative
subset and the results are extrapolated to the larger group. In other words,
you can ask a question of a subset of the population and make inferences about
the entire population from the subset's answers. This subset of the population
is called a sample.
Inferential statistics,
however, don't always work as well with geographic data. When this is the case,
descriptive statistics are applied.
The methods of
inferential statistics don't transfer easily to geographic data for two main
reasons. First, inferential statistics assume that you want to estimate the
characteristics of a population from a sample. With geographic data, however,
you often have the entire population to work with, so you use descriptive
statistics rather than inferential statistics.
Second, inferential
statistics does not include tools for representing geographic data.
ArcGIS™ Spatial Analyst provides a
set of statistical functions, which makes descriptive statistics part of your
geographic analysis. For example, you can compare the difference between values
over time, cell-by-cell, or you can construct a statistical filter to weed out
unwanted values. You can also assess past trends or the current status of
features, or reveal the underlying structure of the data.
Comparing raster
datasets using cell statistics
Statistics are useful for
describing certain tendencies in your data. You may want to know the average
value, the highest value, or how many different types of values exist in the
dataset.
For a single raster
dataset, statistics are automatically generated. The minimum, maximum, and mean
values, as well as the standard deviation of values are presented in the
layer’s properties.
You can also use statistics
to create new raster datasets. While the statistical functions are divided into
three basic groups (cell statistics, neighborhood statistics, and zonal
statistics), each group utilizes the same statistical methods.
Cell statistics allow you
to compare two or more raster datasets on a cell-by-cell basis. In other words,
cells occupying the same location but belonging to different rasters can be evaluated together using basic descriptive
statistics. This is especially useful when comparing time-series data, such as
annual changes in land use.
Describing raster datasets using neighborhood and zonal
statistics
While you can use
statistics to compare corresponding cells from different raster datasets, you
can also evaluate a single raster dataset based on neighborhoods or zones.
The Neighborhoods
Statistics function considers the values of cells within a specified
neighborhood around the processing cell. Neighborhoods are sections of the
raster that can be defined in almost any way you want. Neighborhood statistics
are output as new raster layers.
The Zonal Statistics
function considers the values of cells based on groups of like cells, or zones,
in another dataset. Zonal statistics are output as tables.