rasclass: Supervised Raster Image Classification

Software to perform supervised and pixel based raster image classification. It has been designed to facilitate land-cover analysis. Five classification algorithms can be used: Maximum Likelihood Classification, Multinomial Logistic Regression, Neural Networks, Random Forests and Support Vector Machines. The output includes the classified raster and standard classification accuracy assessment such as the accuracy matrix, the overall accuracy and the kappa coefficient. An option for in-sample verification is available.

AuthorDaniel Wiesmann <daniel.wiesmann@tecnico.ulisboa.pt> and David Quinn <djq@urbmet.com>
Date of publication2016-05-02 06:31:45
MaintainerDaniel Wiesmann <daniel.wiesmann@tecnico.ulisboa.pt>
LicenseGPL (>= 2)

View on CRAN


buildFormula Man page
buildFormula,rasclass-method Man page
checkRasclass Man page
checkRasclass,rasclass-method Man page
classifyRasclass Man page
classifyRasclass,rasclass-method Man page
image,rasclass-method Man page
image,rasclassRaster-method Man page
rasclass Man page
rasclass-class Man page
rasclassMlc Man page
rasclassMlc,rasclass-method Man page
rasclass-package Man page
rasclassRaster Man page
rasclassRaster-class Man page
readRaster Man page
readRaster,character-method Man page
readRasterFolder Man page
readRasterFolder,character-method Man page
setRasclassData Man page
setRasclassData,data.frame-method Man page
summary,rasclass-method Man page
View,rasclass-method Man page
writeRaster Man page
writeRaster,rasclassRaster-method Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.