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New package > RStoolbox: Remote Sensing Data Analysis in R

Dear list members,

We are happy to announce the initial release of our *RStoolbox* package.
RStoolbox provides various tools for remote sensing data analysis and is 
now available from CRAN:
    https://cran.r-project.org/web/packages/RStoolbox

The main focus of RStoolbox is to provide a set of high-level remote 
sensing tools for various classification tasks. This includes 
unsupervised and supervised classification with different classifiers, 
fractional cover analysis and a spectral angle mapper. Furthermore, 
several spectral transformations like vegetation indices, principal 
component analysis or tasseled cap transformation are available as well.

Besides that, we provide a set of data import and pre-processing 
functions. These include reading and tidying Landsat meta-data, 
importing ENVI spectral libraries, histogram matching, automatic image 
co-registration, topographic illumination correction and so on.

Last but not least, RStoolbox ships with two functions dedicated to 
plotting remote sensing data (*raster* objects) with *ggplot2* including 
RGB color compositing with various contrast stretching options.

RStoolbox is built on top of the *raster* package. To improve 
performance some functions use embedded C++ code via the *Rcpp* package. 
Moreover, most functions have built-in support for parallel processing, 
which is activated by running raster::beginCluster() beforehand

RStoolbox is hosted at www.github.com/bleutner/RStoolbox

For a more details, including executed examples, please see
http://bleutner.github.io/RStoolbox/rstbx-docu/

We sincerely hope that this package may be helpful for some people and 
are looking forward to any feedback, suggestions and bug reports.

-- 
Benjamin Leutner
Ned Horning