Available statistics are those related to the shape, size and position of the areas (see the r.object.geometry man page for more information on the statistics) and aggregated statistics of pixel values of other raster maps (see r.univar for details).
In addition, for each of the above statistics, the -n flag allows the user to request the output of the mean and the standard deviation of the values of the neighboring objects (all direct neighbors, diagonal neighbors included), which allows gathering some context information for each object. For this feature, the r.neighborhoodmatrix addon has to be installed. Currently, the module calculates these context statistics for all available shape and spectral statistics.
The user can chose between output in the form of a vector map of the areas with the statistics in the attribute table (vectormap) and/or in the form of a CSV text file (csvfile).
Because of the way r.univar functions, it is difficult to handle cases where in some raster maps values are all null in some of the areas. Because of this, i.segment.stats checks the raster maps for existing null values and excludes them if it find any, emitting a warning to inform the user. The user can decide to ignore this check using the c flag, for example when there are only a few null cells and no complete areas with only null cells (i.e. the module can calculate statistics for areas with some null cells in them).
The module respects the current region settings. The -r flag allows to force the module to adjust the region to the input raster map before calculating the statistics.
This module is a simple front-end to r.univar and r.object.geometry. If other statistics are desired, these should probably be implemented in those (or other) modules which can then be called from this module.
Problems can arise in the calculation of some form statistics for certain segment forms. If errors arise, the user might want to try to run r.clump on the input raster file before running i.segment.stats.
When treating files with a large number objects, creating the vector map can be very time-consuming. In that case, it might be easier to only work with the csvfile output.
The processing of several raster input files for which to calculate per-segment statistics can be parallelized by setting the processes parameter to the number of desired parallel processes, with at most one process per raster to be treated.
i.group group=landsat_pan input=lsat7_2002_80 g.region rast=lsat7_2002_80 -p i.segment group=landsat_pan output=ls_pan_seg01 threshold=0.1 memory=4000 minsize=50 i.segment.stats map=ls_pan_seg01 csvfile=segstats.csv vectormap=ls_pan_seg01 \ rasters=lsat7_2002_10,lsat7_2002_20,lsat7_2002_30,lsat7_2002_40,lsat7_2002_50,lsat7_2002_70 \ processes=4
Latest change: Fri Mar 25 13:11:01 2022 in commit: 410afa48c3c8f8a4d5da9e86e4f457c8ec7d4b5f
© 2003-2022 GRASS Development Team, GRASS GIS 8.0.3dev Reference Manual