create_training_data_from_points: Create Training Data from Points
In tabrasel/WetlandTools: General utility functions for TerrainWorks

create_training_data_from_points

R Documentation

Create Training Data from Points

Description

Given an input dataset and set of positive points, generate randomly sampled negative points and extract predictor values for positive and negative points.

Usage

create_training_data_from_points(
  positive_points,
  predictors_raster,
  analysis_region_mask = NULL,
  buffer_radius = 15,
  negative_proportion = 1,
  extraction_method = "centroid",
  extraction_layer = NULL,
  rseed = NULL
)

Arguments

`positive_points`	SpatVector with locations of all points with positive class
`predictors_raster`	SpatRaster with a layer for each predictor variable
`analysis_region_mask`	SpatRaster with non-NA values everywhere that points can be sampled from. All locations that should be excluded from sampling should be NA. If NULL, all cells which are non-NA for all layers of the predictors_raster will be used.
`buffer_radius`	minimum possible distance between a positive and negative point
`negative_proportion`	Proportion of negative points to be generated compared to number of positive points
`extraction_method`	Method to use for extracting values from each point: "all", "centroid", "max", or "min". Ignored if extractionPoints is not polygon
`extraction_layer`	Layer to use for extracting value. Ignored if extraction_method = "centroid". Ignored if extraction_method is "all" or "centroid" or if extractionPoints is not polygon.
`rseed`	Optional integer to seed the random sampling. This allows exact "random" results to be reproduced multiple times. If no number is given, a random number will be chosen as a seed.