Description

The RStoolbox package provides a set of functions which simplify performing standard remote sensing tasks in R. Most functions have built-in parallel support. All that is required is to run beginCluster beforehand.

Data Import and Export

• readMeta: import Landsat metadata from MTL or XML files

• stackMeta: load Landsat bands based on metadata

• readSLI & writeSLI: read and write ENVI spectral libraries

• saveRSTBX & readRSTBX: save and re-import RStoolbox classification objects (model and map)

• readEE: import and tidy EarthExplorer search results

Data Pre-Processing

• radCor: radiometric conversions and corrections. Primarily, yet not exclusively, intended for Landsat data processing. DN to radiance to reflectance conversion as well as DOS approaches

• topCor: topographic illumination correction

• cloudMask & cloudShadowMask: mask clouds and cloud shadows in Landsat or other imagery which comes with a thermal band

• classifyQA: extract layers from Landsat 8 QA bands, e.g. cloud confidence

• rescaleImage: rescale image to match min/max from another image or a specified min/max range

• normImage: normalize imagery by centering and scaling

• histMatch: matches the histograms of two scenes

• coregisterImages: co-register images based on mutual information

• panSharpen: sharpen a coarse resolution image with a high resolution image (typically panchromatic)

Data Analysis

• spectralIndices: calculate a set of predefined multispectral indices like NDVI

• tasseledCap: tasseled cap transformation

• sam: spectral angle mapper

• rasterPCA: principal components transform for raster data

• rasterCVA: change vector analysis

• unsuperClass: unsupervised classification

• superClass: supervised classification

• fCover: fractional cover of coarse resolution imagery based on high resolution classification

Data Display

• ggR: single raster layer plotting with ggplot2

• ggRGB: efficient plotting of remote sensing imagery in RGB with ggplot2