train_rF_classifier_on_polygons: Calibrates A Supervised Classification Of Multiband Imagery...

In pieterbeck/CanHeMonR: Tools for canopy health monitoring through image analysis

Description

Calibrates a supervised classification of multiband imagery data, using reference data (presence/absence) in a polygon shape file

Usage

train_rF_classifier_on_polygons(polygon_SpatDF, calibration_field,
  training_brick, outp_rdata_file)

Arguments

polygon_SpatDF	SpatialPolygonsDataFrame
calibration_field	The field in polygon_SpatDF that contains the classes and serves as response variable for the model.
training_brick	Raster brick from which values are extracted, as predictor variables
outp_rdata_file	Output filename for an rdata object containing the rF model

Value

rF model, also written away to file

Note

TO DO: Provide options with classification (rF, where you have pres/abs training data) and similarity, where you only have pres training data that uses maxent DOES CROPPPING TO COMMON EXTENT SAVE TIME ?

pieterbeck/CanHeMonR documentation built on May 25, 2019, 7:11 a.m.