GRASS files
 

 

 

 

 

 GRASS GIS:

Some documentation can be found on my page at Otago: http://bambi.otago.ac.nz/hamish/grass/

o  Scripts and examples of custom raster color map creation.

Tips for building GRASS on Debian GNU/Linux

o  Copy of NNBathy 1.80 interpolation software for r.surf.nnbathy

o  Some NVIZ examples:

 

 


r.in.xyz

The r.in.xyz module will load and bin ungridded x,y,z ASCII data into a new raster map. The user may choose from a variety of statistical methods in creating the new raster.

r.in.xyz is designed for processing massive point cloud datasets, for example raw LIDAR or multibeam sonar swath data. It should work with a dataset of any size; currently the largest known success is a 379GB file (ran overnight to process 14.5 billion data points).

Detailed information is available on the help page.



 

 

  The r.in.xyz GUI control window.





        [click on images to enlarge]

 

Here are some shots of the Jockey's Ridge, NC, LIDAR dataset after r.in.xyz post-processing.
Roads, houses, ocean waves parallel to the beach, and highway lightpoles are clearly visible.
Google blurs the images a little (even the .png files) - the originals are infact substantially clearer -
you can even see traffic lights and cars. Compare with the Google Maps satellite view.

     

     

     "n" map containing scans per cell.




     

    "min" map interpolated into a surface using
    regularized splines (via r.to.vect and v.surf.rst).



     

     

     NVIZ representation of above xyz.min.rst map.

 

 

Sidescan and multibeam sonar folks might also be interested in:

  • The v.swathwidith module by David Finlayson for planning surveys. (development page)
  • An example of post-processing scanned paper sidescan swaths using thin plate spline warping with GDAL's "gdalwarp -tps" function. (debugging page)
  • MBSystem open source software from MBARI and Columbia Univ's Lamont-Doherty EO for the processing and display of swath sonar data.

LIDAR folks might also be interested in:

  • r.terraflow - computation of flow direction, flow accumulation and other basic topographic terrain indices from massive raster digital elevation models (DEM). From the Duke University STREAM project.
  • Flood simulation using r.lake. Includes fancy NVIZ visualization of Trento, Italy, by Markus Neteler.