spatialGreen: Process pixel-based greenness indexes

In gianlucafilippa/phenopix: Process Digital Images of a Vegetation Cover

Description

This function allows to filter, fit a curve and extract thresholds in a pixel-based analysis exactly as autoFilter and greenProcess do in a ROI-based analysis, except that uncertainty cannot be estimated (since it would be too computationally intense)

Usage

spatialGreen(filtered.data, fit, threshold, ncores='all', 
  log.file=NULL)

Arguments

filtered.data	A list as in output from spatialFilter().
fit	A character vector of length 1. Available options are: spline, beck, elmore, klosterman, gu.
threshold	A character vector of length 1. Available options are: spline, derivatives, klosterman, gu.
ncores	Number of processors to be used in parallel computation, defaults to 'all' which will accidentally slow down any other activity on your computer. Otherwise set the number of processors you want to use in parallelization.
log.file	It can be NULL or a path where to generate and refresh a txt file which logs the progress of the filtering procedure

Details

This function allows to fit a curve and extract thresholds in a pixel-based analysis exactly as greenProcess does in a ROI-based analysis, except that uncertainty cannot be estimated (since it would be too computationally intense). This function takes as first argument a list as in output from spatialFilter. For each pixel in the ROI the function fits a curve (according to options specified in fit) and extracts thresholds (as defined in threshold). This function performs the same task that greenProcess does in a ROI-based analysis, except that uncertainty cannot be estimated (since it would be too computationally intense). For pixel-based analysis, it is recommended to use rather low resolution images or split your region of interest into multiple subROIs (function splitROI. A specific vignette for spatial analysis is stored as pdf in the package folder. The user is adviced to carefully read it before starting a spatial analysis.

Author(s)

Gianluca Filippa <[e-mail]>

gianlucafilippa/phenopix documentation built on Nov. 4, 2019, 1:06 p.m.