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NAME

i.sentinel_2.autotraining - Automatically generates training data from input bands and indices a reference classification and treecover map. Creates classes water, low vegetation, forest, bare soil and built-up.

KEYWORDS

imagery, satellite, Sentinel, classification, extraction

SYNOPSIS

i.sentinel_2.autotraining
i.sentinel_2.autotraining --help
i.sentinel_2.autotraining ndvi=name ndwi=name ndbi=name [bsi=name] ref_classification_probav=name ref_treecover_fraction_probav=name [ref_classification_gong=name] ref_ghs_built=name [percentage_threshold=float] output_vector=name output_raster=name [str_column=string] [int_column=string] npoints=integer [--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:

ndvi=name [required]
Input NDVI raster map
ndwi=name [required]
Input NDWI raster map
ndbi=name [required]
Input NDBI raster map
bsi=name
Input BSI raster map
ref_classification_probav=name [required]
Input reference probav classification map
ref_treecover_fraction_probav=name [required]
Input reference probav treecover fraction map
ref_classification_gong=name
Input reference gong et al. classification map
ref_ghs_built=name [required]
Input reference global human settlement builtup map (GHS-BUILT)
percentage_threshold=float
Minimum percentage of area potential training data of a class has to cover to be included in the classification
Options: 0.0-50.0
Default: 0.1
output_vector=name [required]
Output vector map with training data points. Class information will be stored in columns str_column and int_column
output_raster=name [required]
Output raster map with potential training areas
str_column=string
Name of the string column in output_vector to store class information
Default: lulc_class_str
int_column=string
Name of the integer column in output_vector to store class information
Default: lulc_class_int
npoints=integer [required]
Number of sampling points per class in the output vector map
Default: 10000

Table of contents

DESCRIPTION

i.sentinel_2.autotraining is a GRASS addon that automatically creates raster and vector training/validation data for further classification. It covers the classes water, low vegetation, forest, bare soil and built-up.

EXAMPLE

i.sentinel_2.autotraining ndvi=ndvi ndwi=ndwi ndbi=ndbi bsi=bsi \
  ref_classification=PROBAV_classification_Borneo \
  ref_treecover_fraction=PROBA_V_100m_treecoverfraction \
  percentage_threshold=0.1 npoints=1000 output_vector=test_autotraining_vector \
  output_raster=test_autotraining_raster

SEE ALSO

r.mapcalc, r.patch, r.sample.category

AUTHOR

Guido Riembauer, mundialis GmbH & Co. KG

SOURCE CODE

Available at: i.sentinel_2.autotraining source code (history)

Accessed: Thursday Aug 15 12:57:16 2024


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