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NAME

v.incora.training_data - Creates a vector map containing training points from a set of rules.

KEYWORDS

vector, classification, training data

SYNOPSIS

v.incora.training_data
v.incora.training_data --help
v.incora.training_data imperviousness=name landcover=name elevation=name ndvi_max=name ndvi_min=name ndvi_range=name ndwi=name coastline=name buildings=name roads=name water=name blue=name green=name red=name npoints=integer output=name [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

--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:

imperviousness=name [required]
Input imperviousness raster map
From here: https://land.copernicus.eu/pan-european/high-resolution-layers/imperviousness/status-maps/2015
landcover=name [required]
Input landcover raster map
From here: http://s2glc.cbk.waw.pl/extension
elevation=name [required]
Input digital elevation model
Used to remove builtup training data in high altitudes
ndvi_max=name [required]
Input NDVI_maximum raster map from NDVI timeseries
Name of input raster map
ndvi_min=name [required]
Input NDVI_minimum raster map from NDVI timeseries
Name of input raster map
ndvi_range=name [required]
Input NDVI_range raster map from NDVI timeseries
Name of input raster map
ndwi=name [required]
Input NDWI raster map
Name of input raster map
coastline=name [required]
Input coastline raster map
Name of input raster map
buildings=name [required]
Input OSM buildings raster map
Downloaded from Geofabrik, reprojected using ogr2ogr, rasterized using gdal_rasterize
roads=name [required]
Input OSM roads raster map
Downloaded from Geofabrik, reprojected using ogr2ogr, rasterized using gdal_rasterize
water=name [required]
Input OSM water raster map
Downloaded from Geofabrik, reprojected using ogr2ogr, rasterized using gdal_rasterize
blue=name [required]
Input blue band
Blue band of input satellite image
green=name [required]
Input green band
Green band of input satellite image
red=name [required]
Input red band
Red band of input satellite image
npoints=integer [required]
Number of sampling points per class in the output vector map
output=name [required]
Name of output vector map containing training points
Name for output vector map

Table of contents

DESCRIPTION

v.incora.training_data creates a vector map containing training points from a set of rules. Output classes (incora) are:

EXAMPLE

v.incora.training_data imperviousness=HRL_Imperviousness_null \
landcover=S2GLC_Europe_2017_v1.2 ndvi_max=maja_2019_NDVI_maximum_Mar_May_Jul_Sep \
ndvi_min=maja_2019_NDVI_minimum_Mar_May_Jul_Sep \
ndvi_range=maja_2019_NDVI_range_Mar_May_Jul_Sep \
ndwi=July19_NDWI ndbi=July19_NDBI asm=July19_asm_ASM \
buildings=NRW_OSM_buildings_rast_10m roads=NRW_OSM_roads_rast_10m \
npoints=10000 output=incora_training_auto_2019

SEE ALSO

r.sample.category, r.buffer, r.mapcalc, r.mask, r.quantile

AUTHORS

Guido Riembauer, mundialis Anika Weinmann, mundialis

SOURCE CODE

Available at: v.incora.training_data source code (history)

Accessed: Tuesday Apr 23 08:19:01 2024

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