r.statistics - GRASS GIS manual

Note: This document is for an older version of GRASS GIS that will be discontinued soon. You should upgrade, and read the current manual page.

NAME

r.statistics - Calculates category or object oriented statistics.

KEYWORDS

raster, statistics, zonal statistics

SYNOPSIS

r.statistics

r.statistics --help

r.statistics [-c] base=name cover=name method=string output=name [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

-c: Cover values extracted from the category labels of the cover map
--overwrite: Allow output files to overwrite existing files
--help: Print usage summary
--verbose: Verbose module output
--quiet: Quiet module output
--ui: Force launching GUI dialog

Parameters:

base=name [required]: Name of base raster map
cover=name [required]: Name of cover raster map
method=string [required]: Method of object-based statistic; Options: diversity, average, mode, median, avedev, stddev, variance, skewness, kurtosis, min, max, sum; diversity: Diversity of values in specified objects in %%; average: Average of values in specified objects; mode: Mode of values in specified objects; median: Median of values in specified objects; avedev: Average deviation of values in specified objects; stddev: Standard deviation of values in specified objects; variance: Variance of values in specified objects; skewness: Skewnes of values in specified objects; kurtosis: Kurtosis of values in specified objects; min: Minimum of values in specified objects; max: Maximum of values in specified objects; sum: Sum of values in specified objects
output=name [required]: Resultant raster map

DESCRIPTION
NOTES
EXAMPLES
SEE ALSO
AUTHOR

DESCRIPTION

r.statistics is a tool to analyse exploratory statistics of a categorical "cover layer" according to how it intersects with objects in a "base layer". A variety of standard statistical measures are possible (called "zonal statistics" in some GIS). All cells in the base layer are considered one object for the analysis. For some applications, one will first want to prepare the input data so that all areas of contiguous cell category values in the base layer are uniquely identified, which can be done with r.clump.
The available methods are the following:

average deviation
average
diversity
kurtosis
maximum
median
minimum
mode
skewness
standard deviation
sum
variance

The calculations will be performed on each area of data of the cover layers which fall within each unique value, or category, of the base layer.

Setting the -c flag the category labels of the covering raster layer will be used. This is nice to avoid the GRASS limitation to integer in raster maps because using category values floating point numbers can be stored.

All calculations create an output layer. The output layer is a reclassified version of the base layer with identical category values, but modified category labels - the results of the calculations are stored in the category labels of the output layer.

NOTES

For floating-point cover map support, see the alternative r.stats.zonal. For quantile calculations with support for floating-point cover maps, see the alternative r.stats.quantile.

EXAMPLES

Calculation of average elevation of each field in the Spearfish region:

r.statistics base=fields cover=elevation.dem out=elevstats method=average
r.category elevstats
r.mapcalc "fieldelev = @elevstats"
r.univar fieldelev

AUTHOR

Martin Schroeder, Geographisches Institut Heidelberg, Germany

SOURCE CODE

Available at: r.statistics source code (history)

Latest change: Mon Nov 18 20:15:32 2019 in commit: 1a1d107e4f6e1b846f9841c2c6fabf015c5f720d