[R-sig-Geo] New package > RStoolbox: Remote Sensing Data Analysis in R

[Sarah Goslee]

And also the landsat package, also on CRAN.

Sarah

On Tue, Sep 15, 2015 at 1:11 PM, Tim Appelhans <tim.appelhans at gmail.com> wrote:
> Benjamin,
> I think we should put our heads together at some stage as we have already
> something very similar on CRAN (released in July)
>
> https://cran.r-project.org/web/packages/satellite/index.html
>
> The satellite package provides standard class(es) and methods for handling
> satellite data. We deliberately avoided adding any functionality that goes
> beyond basic image preparation (i.e. classification or prediction
> capabilities). The idea is to provide a standard package for remote sensing
> data handling (satellite) on top of which other packages can be built to
> provide further functionality (such as the numerous classification
> algorithms in RStoolbox). Think of it as the 'sp' package for satellite
> remote sensing data analysis.
>
> To get a better idea of how satellite is designed please have a look at the
> following vignette (which is not quite finished but does provide an overview
> of how the 'satellite' class is defined).
>
> https://github.com/environmentalinformatics-marburg/satellite/blob/develop/vignettes/satellite.Rmd
>
> I would appreciate your thoughts (maybe off-list) on how to best arrange our
> efforts in order to avoid duplication and confusion for other users.
>
> Best
> Tim
>
> On 14.09.2015 08:36, Benjamin Leutner wrote:
>>
>> 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.
>>
>
> --
> #####################################
> Tim Appelhans
> Department of Geography
> Environmental Informatics
> Philipps Universität Marburg
> Deutschhausstraße 12
> 35032 Marburg (Paketpost: 35037 Marburg)
> Germany
>
> Tel +49 (0) 6421 28-25957
>
> http://environmentalinformatics-marburg.de/
>


-- 
Sarah Goslee
http://www.functionaldiversity.org