New R package: RStoolbox: Tools for Remote Sensing Data Analysis

New R package: RStoolbox: Tools for Remote Sensing Data Analysis

m

September 18, 2015

RStoolbox_RemoteSensing_Ecology_Benjamin_LeutnerWe are happy to announce the initial release of our *RStoolbox* package. The package has been developed by our PhD student Benjamin Leutner and will be used extensively in the upcoming book “Remote Sensing and GIS for Ecologists – Using Open Source software“.
RStoolbox provides various tools for remote sensing data analysis and is now available from CRAN:

https://cran.r-project.org/web/packages/RStoolbox

and more details at:

http://bleutner.github.io/RStoolbox/rstbx-docu


 

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.

you may also like:

Contribution at SilviLaser Conference in Quebec

Contribution at SilviLaser Conference in Quebec

At SilviLaser 2025 in Québec City, PhD candidate Julia Rieder (EORC, University of Würzburg and staff member of EO4CAM) presented her work on "European Beech under Drought: Effects of Topography, Competition and Soil Water Availability." Her study uses LiDAR to reveal...

EORC at Remote Sensing Symposium in Darmstadt

EORC at Remote Sensing Symposium in Darmstadt

On 2 October 2025, Dr. John Friesen and Dr. Julian Fäth from the Earth Observation Research Cluster (EORC) at the University of Würzburg and staff members of EO4CAM took part in the symposium "Vom Orbit zur Entscheidung: Satellitenfernerkundung in der...

New Team Member at the EORC: Sonja Mass

New Team Member at the EORC: Sonja Mass

Sonja Maas joined the Earth Observation Research Cluster (EORC) in October 2025 as a research assistant for the EO4CAM project. After finishing her bachelor's degree in forestry, Sonja Maas enrolled in the EAGLE M.Sc. program at the University of Würzburg, where she...

EAGLE MSc Student Isabella Metz Wins Prestigious IFHS Student Award

EAGLE MSc Student Isabella Metz Wins Prestigious IFHS Student Award

We are delighted to share the exciting news that our MSc student Isabella Metz has been awarded the 2025 International Federation of Hydrographic Societies (IFHS) Student Award for her outstanding research on: “Analysis of Uncertainties for Error Detection and...

Josipa Subotic joined as a DBU fellow

Josipa Subotic joined as a DBU fellow

We are delighted to welcome Josipa Subotić to the Earth Observation Research Cluster as a DBU fellowship visiting researcher. Since September 2025, she has been working on her project “Detection of Snow Surfaces in the Alps Using Multispectral Satellite Images and...