RSAGA: Getting Started

March 30, 2013

(This article was first published on Misanthrope's Thoughts, and kindly contributed to R-bloggers)

RSAGA provides access to geocomputation capabilities of SAGA GIS from within R environment. Having SAGA GIS installed is a (quite obvious) pre-requirement to use RSAGA. 
In Linux x64 sometimes additional preparations are needed. In Linux SAGA as well as other software that would like to use SAGA modules usually searches for  them in /usr/lib/saga, but if your Linux is x64, they usually will be located in /usr/lib64/saga. Of course you may set up proper environmental variables, but the most lazy and overall-effective way is just to add symbolic link to /usr/lib64/saga (or whatever a correct path is) from /usr/lib/saga:

:~> sudo ln -s /usr/lib64/saga /usr/lib/saga
Now no app should miss these modules.

Let’s to set up an environment in R.
> library(RSAGA)

# set up rsaga environment:
> work_env <- rsaga.env() 
> work_env 
$workspace [1] "." 
$cmd [1] "saga_cmd" 
$path [1] "/usr/bin" 
$modules [1] "/usr/lib/saga" 
$version [1] "2.0.8"

Note that in this case modules appeared to be located in /usr/lib when they are actually in /usr/lib64. Thanks to the symbolic link, we don’t have to provide RSAGA with the real location. If you need to set up detailed environmental parameters run:
> work_env <- rsaga.env(workspace='path_to_your_folder',
+                       path = '/usr/bin',
+                       modules = '/usr/lib64/saga')

It’s time to get the list of available libraries (sets of modules):

> rsaga.get.libraries() 
 [1] "contrib_a_perego"            "docs_html" 
 [3] "docs_pdf"                    "garden_3d_viewer" 
 [5] "garden_webservices"          "geostatistics_grid" 
 ...and so on

Each library has a number of modules inside. And we will use modules, not libraries in geoprocessing. Let’s get a list of modules inside one of the library:
> rsaga.get.modules('grid_filter') 

   code                       name interactive
1     0              Simple Filter       FALSE
2     1            Gaussian Filter       FALSE
3     2           Laplacian Filter       FALSE
4     3 Multi Direction Lee Filter       FALSE
5     4        User Defined Filter       FALSE
6     5              Filter Clumps       FALSE
7     6            Majority Filter       FALSE
8     7   DTM Filter (slope-based)       FALSE
9     8       Morphological Filter       FALSE
10    9                Rank Filter       FALSE

In column ‘name’ we have a module name; column ‘interactive’ indicates whether this module is interactive, and column ‘code’ contains the code to be used when the module is called. Now we would like for example to know how to use module ‘DTM Filter (slope-based)’:

> rsaga.get.usage('grid_filter', 7)

Usage: saga_cmd -INPUT <str> [-RADIUS <num>] [-TERRAINSLOPE <str>] [-STDDEV] -GROUND <str> -NONGROUND <str>
  -INPUT:<str>       Grid to filter
Grid (input)
  -RADIUS:<num>       Search Radius
Minimum: 1.000000
  -TERRAINSLOPE:<str> Approx. Terrain Slope
Floating point
Minimum: 0.000000
  -STDDEV             Use Confidence Interval
  -GROUND:<str>       Bare Earth
Grid (output)
  -NONGROUND:<str>   Removed Objects
Grid (output)

library path: /usr/lib/saga
library name: libgrid_filter
module name : DTM Filter (slope-based)

Now we have detailed information about parameters we have to provide as well as data types that these parameters must have. But before we proceed, we have to prepare the data. RSAGA will accept only grid formats for processing, so one have to convert data to suitable format:
> rsaga.import.gdal('lidar.tif')

As a result ‘lidar.srgd’ file will be created in the same folder as original file.

Finally we are ready to execute our first RSAGA geoprocessing command:
rsaga.geoprocessor(‘grid_filter’, module = 7, 
+                    env = work_env,
+                    param = list(INPUT = ‘lidar.sgrd’,
+                                 RADIUS = 20,
+                                 TERRAINSLOPE = 0,
+                                 STDDEV = T,
+                                 GROUND = ‘ground’,
+                                 NONGROUND = ‘non_ground’)
+                    )

Instead of conclusion

RSAGA has a certain degree of inconvenience in usage. It only works with files in .srgd format and both input and output have to be physically stored on your hard drive. So it is better to use it [instead of the SAGA itself] only for routine tasks. 

To leave a comment for the author, please follow the link and comment on their blog: Misanthrope's Thoughts. offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.


Mango solutions

RStudio homepage

Zero Inflated Models and Generalized Linear Mixed Models with R

Dommino data lab

Quantide: statistical consulting and training



CRC R books series

Six Sigma Online Training

Contact us if you wish to help support R-bloggers, and place your banner here.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)