classify_maxent_output_based_on_error_stats: Classify maxent output to binary presence absence maps

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

Description

Classify maxent output to binary presence absence maps based on thresholds of pixel-level probability, expected minimum crown size, and clump size

Usage

classify_maxent_output_based_on_error_stats(r_pred_dir, tile = "ALL",
  max_permittable_cutoff_final = max_permittable_cutoff_final,
  max_permittable_cutoff_npix_final = max_permittable_cutoff_npix_final,
  radius = 0.75, outp_dir, parallel = F, nWorkers = 4)

Arguments

r_pred_dir	A directory where binary .tifs predicting presence as 1 and absence as 0 can be found for multiple tiles
tile	Character vector. Names of tile(s) to run. 'ALL will run all tiles in r_pred_dir. Default is 'ALL'
max_permittable_cutoff_final	Cutoff-level for Maxent probability output. Typically produced by error_summaries.R
max_permittable_cutoff_npix_final	Cutoff-level for the nr of pixels (clumpsize) of presence that a circles of radius radius needs to contain to be maintained as presence. Typically produced by error_summaries.R
radius	The radius of the disk in which clump size is counted
parallel	Should the code be run in parallel using the doParallel package? Default is FALSE.
nWorkers	If running the ocde in parallel, how many workers should be used? Default is 4.

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