How Block Statistics works

The Block Statistics tool performs a neighborhood operation that calculates a statistic for input cells within a fixed set of non-overlapping windows or neighborhoods. The statistic (for example, maximum, average, or sum) is calculated for all input cells contained within each neighborhood. The resulting value for an individual neighborhood or block is assigned to all cell locations contained in the minimum bounding rectangle of the specified neighborhood.

Since the neighborhoods do not overlap, any particular cell will be included in the calculations for one block only.

The shape of a neighborhood can be an annulus (a donut), circle, rectangle, or wedge. The possible statistics that can be calculated within a neighborhood are mean, majority, maximum, median, minimum, minority, range, standard deviation, sum, and variety.

Conceptually, the Block Statistics tool works as follows:

Neighborhood types

The shape of a neighborhood can be an annulus (a donut), circle, rectangle, or wedge. By using a kernel file, you can also define a custom neighborhood shape, as well as assign different weights to specific cells in the neighborhood before the statistic is calculated.

Following is a discussion of the different neighborhood shapes and how they are defined:

Statistics type

The available statistics are majority, maximum, mean, median, minimum, minority, range, standard deviation, and sum. The default statistics type is mean.

Processing cells of NoData

The Ignore NoData in calculations option controls how NoData cells within the neighborhood window are handled. When this option is checked (the DATA option), any cells in the neighborhood that are NoData will be ignored in the calculation of the output cell value. When unchecked (the NODATA option), if any cell in the neighborhood is NoData, the output cell will be NoData.

Uses for block statistics

The Block Statistics tool can be used instead of the Resample tool to resample a raster from a fine resolution to a coarser one. Instead of using the nearest neighbor, bilinear, or cubic resampling techniques, it may be preferable to assign the coarser raster cells the maximum, minimum, or average of the values in the new geographic extent that the coarser cells encompass. To do so, the appropriate statistics are applied to the block—the average (mean) or maximum, for example.

The Aggregate tool from the Generalization toolset is similar to Block Statistics in that it allows for the aggregation of cell locations based on the sum, mean, median, or minimum or maximum values within a spatial window, which is determined by the desired output resolution. There are two major differences between the two options, however:

Related Topics

4/10/2014