table of contents
r.statistics(1grass) | GRASS GIS User's Manual | r.statistics(1grass) |
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:¶
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¶
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
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
SEE ALSO¶
r.category, r.clump, r.mode, r.mapcalc, r.neighbors, r.stats.quantile, r.stats.zonal, r.univar
AUTHOR¶
Martin Schroeder, Geographisches Institut Heidelberg, Germany
SOURCE CODE¶
Available at: r.statistics source code (history)
Accessed: Saturday Jul 27 17:08:22 2024
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