[GRASS-dev] GSOC Horizon based voxel interpolation wk 7 checkin

[Sören Gebbert]

Hi Tim,
Can you please check your commits into your Google code repo? It seems to
me that there are some parts of your files missing? Besides of that, can
you please provide manpages for your modules so that we can see what they
are designed for?

It is important for us to be able to run your modules.

Best regards
Soeren
Am 01.08.2013 07:28 schrieb "Tim Bailey" <timibly at gmail.com>:

> Hi Folks
> I worked through the weekend, I am going to have limited internet access
> at the end of the week, and I am working under a rather clear mentor
> ultimatum, So here is my week 7 report.
>
> This week I implemented the voronoi operator, that had confounded me for
> much of July, through a two stage iterative process.  Process A propagates
> identities vertically up profiles from horizon boundaries. Process B
> propagates identities horizontally away from the profiles.
> I applied this to one of my experimental sandboxes that was built for a
> study of late holocene co-seismic subsidence in a coastal saltmarsh. In
> this circumstance coastal marshes exhibit extreme sensitivity to their
> elevation above sea level.  A series of earthquakes during the past 4500
> years are recorded by the sedimentary record at the coastal margins. These
> earthquakes resulted in subsidence events of almost a meter and a half in
> one episode, and notable movement in several other events. In addition the
> introduction of tsunami, and mudflat deposits overlaying peat deposits
> create a very appealing paleo environment to reconstruct using voxel
> operators.The GRASS region was bound between the deepest core at 6 meters
> below sea level and 3 meters above, which was clearly out of the range of
> the modern salt marsh. On my computer with an amd5700 processor, 12gb ram,
> with ssd, Ubuntu 13.04 and GRASS7,process A takes 12 seconds per
> iteration,  and process B takes 22 seconds per iteration for a 32,000,000
> voxel map. From the data that I am working with process A required 9
> iterations and process B required 50 cycles. Region anisotropy was set to
> 10:1, where it could really comfortably be 100:1.  Nonetheless, this is not
> that different from the computing demands of moderately large lidar job.
> Also in this case iteration limits can be used to limit the area of
> influence of a data point.
>
> Next week will work on refining this weeks work and implement a surface
> limit.
>
> Tim Bailey
>
>
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