The RStoolbox package provides a set of functions which simplify performing standard remote sensing tasks in R.
readMeta: import Landsat metadata from MTL or XML files
stackMeta, getMeta: 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
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
encodeQA & decodeQA: encode/decode Landsat 16-bit QA bands.
rescaleImage: rescale image to match min/max from another image or a specified min/max range
normImage: normalize imagery by centering and scaling
oneHotEncode: one-hot encode a raster or vector
histMatch: matches the histograms of two scenes
pifMatch: matches one scene to another based on linear regression of Pseudo-Invariant Features (PIF)
coregisterImages: co-register images based on mutual information
panSharpen: sharpen a coarse resolution image with a high resolution image (typically panchromatic)
estimateHaze: estimate image haze for Dark Object Subtraction (DOS)
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
rasterEntropy: calculates shannon entropy
unsuperClass: unsupervised classification
superClass, validateMap, getValidation: supervised classification and validation
fCover: fractional cover of coarse resolution imagery based on high resolution classification
mesma: spectral unmixing using Multiple Endmember Spectral Mixture Analysis (MESMA)
ggR: single raster layer plotting with ggplot2
ggRGB: efficient plotting of remote sensing imagery in RGB with ggplot2