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RStoolbox

RStoolbox is an R package providing a wide range of tools for your every-day remote sensing processing needs. The available tool-set covers many aspects from data import, pre-processing, data analysis, image classification and graphical display. RStoolbox builds upon the raster package, which makes it suitable for processing large data-sets even on smaller workstations. Moreover in most parts decent support for parallel processing is implemented.

For more details have a look at the functions overview.

Installation

The package is now on CRAN and can be installed as usual via

install.packages("RStoolbox")

To install the latest version from GitHub you need to have r-base-dev (Linux) or Rtools (Windows) installed. Then run the following lines:

library(devtools)
install_github("bleutner/RStoolbox")

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Version

Install

install.packages('RStoolbox')

Monthly Downloads

2,089

Version

0.2.3

License

GPL (>= 3)

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/bleutner/RStoolbox

Homepage

http://bleutner.github.io/RStoolbox

Maintainer

Benjamin Leutner

Last Published

June 22nd, 2018

Functions in RStoolbox (0.2.3)

Tidy import tool for EarthExplorer .csv export files

Plot RasterLayers in ggplot with greyscale

Write ENVI spectral libraries

Topographic Illumination Correction

Tasseled Cap Transformation

Read Landsat MTL metadata files

Change Vector Analysis

Set global options for RStoolbox

Radiometric Calibration and Correction

Spectral Angle Mapper

Save and Read RStoolbox Classification Results

Principal Component Analysis for Rasters

Multi-layer Pixel Entropy

Rlogo as RasterBrick

Pseudo-Invariant Features based Image Matching

predict.superClass

Predict a raster map based on a superClass model fit.

Linear Image Rescaling

Read ENVI spectral libraries

SRTM Digital Elevation Model

spectralIndices

Spectral Indices

Supervised Classification

Import separate Landsat files into single stack

Map accuracy assessment

Unsupervised Classification

ImageMetaData Class

RStoolbox: A Collection of Remote Sensing Tools

Landsat 5TM Example Data

Multiple Endmember Spectral Mixture Analysis (Spectral Unmixing)

Image to Image Contrast Matching

Create ggplot2 Raster Plots with RGB from 3 RasterLayers

Estimate Image Haze for Dark Object Subtraction (DOS)

Fractional Cover Analysis

Extract validation results from superClass objects

Decode QA flags to bit-words

Encode QA Conditions to Integers

Fortify method for classes from the raster package.

cloudShadowMask

Cloud Shadow Masking for Flat Terrain

coregisterImages

Image to Image Co-Registration based on Mutual Information

Extract bandwise information from ImageMetaData

Normalize Raster Images: Center and Scale

Pan Sharpen Imagery / Image Fusion

Simple Cloud Detection

Classify Landsat8 QA Band