[GRASS-dev] GSOC Horizon based stratigraphy

Pierre Roudier pierre.roudier at gmail.com
Thu Jun 27 02:45:59 PDT 2013


Hi Ben,

You are right, these mass-preserving splines are for continuous data -
it seems I have been carried away from the original scope of the
project while writing my email :)

Cheers,


P

2013/6/27 Benjamin Ducke <benducke at fastmail.fm>:
> On 06/26/2013 06:48 PM, Pierre Roudier wrote:
>>
>> Hi all,
>>
>>
>>> This is an excellent point. While I like the mention of AQP in this
>>> context,
>>> I totally support a GRASS-based implementation with as few dependencies
>>> as
>>> possible.
>>
>>
>> +1 - I think a native GRASS implementation would make a lot of sense.
>>
>>>> Yes, the thought of such "waffel voxels" is not exactly appealing.
>>>> However, they may be a smaller problem in practice, since the voxel
>>>> models themselves are often used to derive vertical slices
>>>> ("profiles"), and those might look perfectly fine, even if derived
>>>> from malformed voxels. GRASS does allow for individual X, Y and Z
>>>> dimensions of voxels, so there is no technical problem with this.
>>>> The results of the interpolation don't need to be beautiful, they
>>>> just need to be as accurate and as true to the data as possible.
>>>>
>>
>> That's the very nature of soils data - we soil scientists often deal
>> with pixels of 10 to 500m resolution, to observe processes that occur
>> generally in the first meter in the z axis! It is not a problem, and
>> the challenge is to come up with tools that allow us to store, query
>> and interpolate such data.
>>
>>> This is a popular topic in the soils literature-- vertical anisotropy can
>>> be
>>> an order of magnitude greater than what is found in the horizontal.
>>> Restricted cubic splines have some desirable characteristics for dealing
>>> with this kind of data-- however, these work best in the context of a
>>> regression model. Also, there are the mass-preserving splines that are
>>> more
>>> useful in the "interpolation along the soil profile" sense. For
>>> categorical
>>> data, I would recommend the ordinal-ratio logistic regression model,
>>> which
>>> generates class-wise probability estimates. I have found this quite
>>> useful
>>> for generating probability depth-functions for categorical soil
>>> properties.
>>> I can elaborate as needed.
>>
>>
>> The mass-preserving splines has become a key tool in the GlobalSoilMap
>> project. An implementation in R exists but is not very efficient. This
>> could be an opportunity to come up with a reference implementation! As
>> mentioned by Dylan, various interpolation methods are available,
>> restricted cubic splines look good as well.
>>
>
> But is that method suitable for categorized input data?
> Or does it only work for continuous soil properties?
> A spline-based interpolator from 3D vector to 3D raster
> already exists in GRASS (v.vol.rst).
>
> Best,
>
> Ben
>
>>
>> Cheers,
>>
>> P
>>
>
>
>
> --
> Dr. Benjamin Ducke, M.A.
> {*} Geospatial Consultant
> {*} GIS Developer
>
>   benducke at fastmail.fm
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-- 
Scientist
Landcare Research, New Zealand


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