rasclass: Supervised Raster Image Classification
Version 0.2.2

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.

Package details

AuthorDaniel Wiesmann <[email protected]> and David Quinn <[email protected]>
Date of publication2016-05-02 06:31:45
MaintainerDaniel Wiesmann <[email protected]>
LicenseGPL (>= 2)
Version0.2.2
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("rasclass")

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rasclass documentation built on May 29, 2017, 7:21 p.m.