The link2GI package provides a small linking tool to simplify the usage of
Orfeo Toolbox (
GDAL binaries for R users. the focus is to simplify the the accessibility of this software for non operating system specialists or highly experienced GIS geeks. Acutally it is a direct result of numerous graduate courses with R(-GIS) beginners in the hostile world of university computer pools running under extremely restricted Windows systems.
link2GIaccording to specific system requirements
R has quite a lot of classes for storing and dealing with spatial data. For vector data the sp and recently the great sf packages are well known and the raster data world is widely covered by the raster package. Additionally external spatial data formats are interfaced by wrapping packages as rgdal or gdalUtils. For more specific links as needed for manipulating atmospheric modeling packages as ncdf4 are very helpful.
The spatial analysis itself is often supported by wrapper packages that integrate external libraries, command line tools or a mixture of both in an R-like syntax rgeos, geosphere, Distance, maptools, igraph or spatstat.
A comprehensive introduction to the spatial R-biotope and its backgrounds is excellently treated in Geocomputation with R wich is highly recommend as a reference textbook.
Despite all this capabilities of spatial analysis and data handling in the world of
R, it can be stated (at least from a non-R point of view), that there is still a enormous gap between R and the mature open source Geographic Information System (GIS) and even more Remote Sensing (RS) software community.
GRASS GIS and
SAGA GIS are providing a comprehensive, growing and mature collection of highly sophisticated algorithms. The provided algorithms are fast, stable and most of them are well proofed. Probably most of the
R users who are somehow related to the GI community know that there are awesome good wrapper packages for bridging this gap. For GRASS GIS 7 it is rgrass7 and for SAGA GIS the RSAGA package. The development of the RQGIS wrapper is the most recent outcome to provide a simple usage of the powerful QGIS command line interface.
In addition there is no wrapper for the great
OTB. It seems to be at least convenient to provide a lightweight wrapping utility for the usage of
OTB modules from
Unfortunately one will run into a lot of technical problems depending on the choosen operating system (OS) or library dependencies or GIS software versions. In case of e.g.
RSAGA the main problem has been that the
SAGA GIS developers are not only changing the syntax and strategy of the command line interface (CLI) but also within the same release the calls differ from OS to OS. So the maintenance of RSAGA is at least laborious (but thumbs up is running again). Another example is given by
GRASS GIS which is well known for a sophisticated setup of the environment and the spatial properties of the database. If you “just” want to use a specific
GRASS algorithm from R, you will probablys get lost in setting up all OS-dependencies that are neccessary to set up a correct temporary or permanent
GRASS-environment from “outside”. This is not only caused due to the strict spatial and projection requirements of
GRASS but much more by challenging OS enviroments especially Windows.
To make it short it is a bit cumbersome to deal with all this stuff if one just want to start e.g.
GRASS from the R command line for e.g. a powerful random walk cost analysis (
r.walk) call as provided by
Linking means simply to provide all necessary environment settings that satisfy the existing wrapper packages as well as in addition the full access to the the command line (CLI) APIs of the mentioned software tools.
link2GI tries to analyze which software is installed to set up an temporary enviroment meeting the above mentioned needs.
GRASS GIS has the most challenging requirements. It needs a bunch of environment and path variables as and a correct setup of the geographical data parameters. The
linkGRASS7 function tries to find all installations let you (optionally) choose the one you want to use and generate the necessary variables. As a result you can use both the rgrass7 package or the command line
SAGA GIS is a far easier to set up. Again the
linkSAGA function tries to find all
SAGA installations, let you (optionally) choose one and generate the necessary variables. You may also use
RSAGA but you have to hand over the result of
RSAGA::rsaga.env(path = saga$sagaPath). For a straightforward usage you may simply use the
R system() call to interface
R with the
Orfeo Toolbox (OTB) is a very powerful remote sensing toolbox. It is widely used for classification, filtering and machine learning applications. You will find some of the implemented algorithm within different R packages but always much slower or only running on small data chunks.
link2GI searches and connects all
OTB installations of a given search path and provides the result as a clear list. Due to a missing wrapper package, a list-based
OTB module and function parser is also available, which can be piped into the function
runOTB for a convenient function call.
GDAL is perfectly integrated in R in some cases it is beneficial to use system calls and grab the binaries directly. In particular the evolution to
GDAL 3.x and optionally various boxed versions of
GDAL binaries working together with different
proj4/proj6 libs makes it sometimes difficult to grab the correct version of
link2GI generates a list of all pathes and commands of all
GDAL installation in the provided search path. With this list, you can easily use all available API calls of each installation.
Automatic search and find of the installed GIS software binaries is performed by the
find functions. Depending of you OS and the number of installed versions you will get a dataframe providing the binary and module folders.
So the most straightforward call to link temporary to
GRASS GIS woud be:
# find all SAGA GIS installations at the default search location require(link2GI) grass <- link2GI::linkGRASS7() grass