New package > RStoolbox: Remote Sensing Data Analysis in R
Hi, @Tim: good to know of your package. I am checking it out right now and will get back to you off-list. The satellite class seems to be exactly what we need and I think we could build on top of it. @Sarah: of course we're aware of the landsat package. However, our students working with smaller workstations frequently encountered memory limitations due to the lack of raster support. Therefore we added a few functions which could be achieved similarly with SpatialPixelsDataFrames and the landsat package if you had enough memory. Benjamin
On 15.09.2015 19:23, Sarah Goslee wrote:
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 Universit?t Marburg Deutschhausstra?e 12 35032 Marburg (Paketpost: 35037 Marburg) Germany Tel +49 (0) 6421 28-25957 http://environmentalinformatics-marburg.de/
Benjamin Leutner M.Sc. Department of Remote Sensing University of Wuerzburg Campus Hubland Nord 86 97074 Wuerzburg, Germany Tel: +49-(0)931-31 89594 Fax: +49-(0)931-31 89594-0 Email: benjamin.leutner at uni-wuerzburg.de Web: http://www.fernerkundung.uni-wuerzburg.de