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

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

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@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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I concur.
Please make sure that your code has been completely
uploaded to the "trunk" folder in your SVN repo.

Also, some sample input data and at least screenshots
of the output that you get would be very helpful.
Preferably, export your result (or a lower resolution
version of it) using r3.out.vtk, zip the VTK file and
upload it to the SVN.

Best,

Ben

On 08/01/2013 08:52 AM, Sören Gebbert wrote:

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@gmail.com
<mailto:timibly@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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    grass-dev@lists.osgeo.org <mailto:grass-dev@lists.osgeo.org>
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--
Dr. Benjamin Ducke, M.A.
{*} Geospatial Consultant
{*} GIS Developer

   benducke@fastmail.fm