RSAGA: Getting Started
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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/sagaNow 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 onEach 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') $grid_filter code name interactive1 0 Simple Filter FALSE2 1 Gaussian Filter FALSE3 2 Laplacian Filter FALSE4 3 Multi Direction Lee Filter FALSE5 4 User Defined Filter FALSE6 5 Filter Clumps FALSE7 6 Majority Filter FALSE8 7 DTM Filter (slope-based) FALSE9 8 Morphological Filter FALSE10 9 Rank Filter FALSEIn 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 Integer Minimum: 1.000000 -TERRAINSLOPE:<str> Approx. Terrain Slope Floating point Minimum: 0.000000 -STDDEV Use Confidence Interval Boolean -GROUND:<str> Bare Earth Grid (output) -NONGROUND:<str> Removed Objects Grid (output)library path: /usr/lib/sagalibrary name: libgrid_filtermodule 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')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.
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