image_regression

Input raster file (independent variable, X).

input1

Input raster file (dependent variable, Y).

input2

Output HTML file for regression summary report.

output

Output raster regression resdidual file.

out_residuals

Optional flag indicating whether to standardize the residuals map.

standardize

Sets verbose mode. If verbose mode is False, tools will not print output messages.

verbose_mode

Performs image regression analysis on two input images.

An R frontend of the 'WhiteboxTools' library, which is an advanced geospatial data analysis platform developed by Prof. John Lindsay at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. 'WhiteboxTools' can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, simple classification (k-means), and common image transformations. 'WhiteboxTools' also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, watershed delineation, stream network analysis, sink removal), terrain analysis (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; hypsometric analysis; multi-scale topographic position analysis), and LiDAR data processing. Suggested citation: Lindsay (2016) <doi:10.1016/j.cageo.2016.07.003>.

image_regression: Image regression

Description

Usage

Arguments

Value