[GIS] How to use SAGA_CMD for batch processing

batchgeotiff-tifflaslidarsaga

I am trying to use SAGA to triangulate a set of .las files I have. I have tiled them using LAStools, since the single file was too big for my computer to handle. I wonder, can I use the saga_cmd grid_gridding "Triangulation" for multiple files, or do I have to process each individually? And I want tif files based on the Z-value, where do I specify the Z value? Is it the -FIELD Attribute?

I have found very little information about the cli scripting of SAGA, are there any book available on the subject?

Best Answer

Yes, you can use saga_cmd grid_gridding Triangulation in a batch file, just like all the other modules. If you want the result files based on the Z-value, you have to specify in the -FIELD attribute.

For a quick example of batch file in SAGA, just type:

saga_cmd -b

All you have to know about the use of SAGA command line (and not only) is described in "Automation of Workflows with SAGA - Command line scripting in a nutshell" of Volker Wichmann. For instance, here you will find:

SAGA | CMD Scripting Example Windows – batch_example.bat (slide 14)
SAGA | CMD Scripting Example GNU/Linux – bash_example.sh (slide 15)

Related Solutions

LAS to DEM Conversion – A Guide

When converting a LiDAR dataset to a DEM, you are taking a set of discrete data points and converting them into a single, continuous dataset. Let's say that your .las file contains X (latitude), Y (longitude) and Z (elevation) values with an average resolution of ~1 meters. The resolution here is really important- we're only talking about an average and so we'll hardly find that ~1 meter resolution throughout the dataset. Instead we'll find values that fall within a 'ballpark' estimate of that resolution. So you take these points and convert them to a raster DEM, or maybe a TIN. X and Y values should see minimum distortion, but you'll notice that your Z values might not be what you expected. This is because the computer doesn't know what the correct Z values are in cells that do not fall on one of your LiDAR points. In between LiDAR points, an interpolation algorithm has been applied to estimate what reasonable Z values might be. Choosing the correct interpolation method relative to the goals of your analysis is a crucial part of going from LiDAR to DEM. Setting the proper resolution on that output DEM is important- always set a lower resolution than the resolution of your LiDAR dataset. So for a ~1 meter resolution I would set a 3 meter resolution for the DEM, in an effort to minimize distortion.

I have experience studying landslides and debris flows with DEMs derived from LiDAR. Landslides and debris flows are very linear features which occur near other linear features in the topography. So when I convert from LiDAR to DEM, I want an interpolation method that best accentuates linear features. This happens to be a TIN (Triangulated Irregular Network). You say that you aim to do a hydrological analysis. Maybe you should try a spline interpolation method to build your DEM. Spline interpolation works be drawing continuous, overlapping lines through all of your data points in order to create a very smooth raster surface. Identify your sinks, fill them, draw countours, repeat.

This is a bit of a ramble, but what I'm trying to get at here is that it seems to me like you're asking the wrong question. Instead of asking for a software workflow you should use to build a hydrologically correct DEM, you should be asking what interpolation method to use. If I were you, I'd try a spline interpolation method.

In terms of software, processing LiDAR data is waaay CPU/RAM intensive. If you have >6 GB of RAM I would recommend GRASS GIS. They've got the best LiDAR processing software I've ever used (it's FOSS), but you have to do some memory allocation. Otherwise, I would recommend sticking with ArcGIS. They've got some great documentation on how to do what you want to do on their website.

[GIS] Fast and robust open source portable script or tool for interpolation – triangulation or similar

The legendary triangulation is available http://www.cs.cmu.edu/~quake/triangle.html

from the page:

I timed the Delaunay triangulation of 1,000,000 vertices uniformly randomly distributed in a square. The output contained 1,999,955 triangles. (I used the -I switch to suppress the rewriting of input vertices to another file, since the vertices written would be identical to the ones read. Hence, only the triangles were written to disk.)

Delaunay triangulation time: 20.761 sec
File output time: 28.794 sec
Total time (above plus file input): 56.115 sec

This has been translated to a python library according to http://dzhelil.info/triangle/index.html# which includes documentation, download https://pypi.python.org/pypi/triangle/2013.04.05 - note, these links may become dead as the version changes. I found them with google in under 10 minutes.

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Related Solutions

LAS to DEM Conversion – A Guide

[GIS] Fast and robust open source portable script or tool for interpolation – triangulation or similar

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