<div dir="ltr">On Mon, Jun 24, 2013 at 10:25 AM, Tim Bailey <span dir="ltr"><<a href="mailto:timibly@gmail.com" target="_blank">timibly@gmail.com</a>></span> wrote:</div><div class="gmail_extra"><div class="gmail_quote">
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><div><div><div><div><div>Hi Pierre, and Hamish <br></div></div><div>It is nice to hear about the onset of Winter in New Zealand. Here in California we are looking at the beginning of a severe season of drought. <br>
<br></div></div></div></div></div></div></blockquote><div><br></div><div>Hi Tim, nice to see another person from CA on the grass-dev list!</div><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div dir="ltr"><div><div><div><div><div></div><div>Clearly the problem of geographic representation of soil properties are quite challenging. The US NRCS distributes soil datasets most often as ArcSDE tables. Not to pander but from my perspective the state of the art tie in with the nrcs data comes from the recent paper Algorithms for quantitative pedology: A toolkit for soil scientists Computers & Geosciences 52 <a href="tel:%282013%29%20258%E2%80%93268" value="+12013258268" target="_blank">(2013) 258–268</a>. I now realize that you Pierre are a coauthor of the article. Nice work by the way. In particular the SoilProfileCollection object specifications are spot on in my opinion. To paraphrase, the minimal horizon description of unique id, top depth, bottom depth, linked to attribute any vertical interval attribute data. <br>
<br></div></div></div></div></div></div></blockquote><div><br></div><div>Totally agree, the NRCS has not done a good job of releasing data in open formats. I am working on changing that, but it might take a while. Efforts like this SoC project are one more way in which soils/geologic data can be opened to a larger audience. Glad to hear you liked the Comp & and GeoSci. article, please do comment/critique as issues arise.</div>
<div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><div><div><div><div>I am just a novice with R but it occurs to me that the soilDB and AQP R
modules might be the best way to generate input point vectors. One capability that I think is particularly useful is the slicing and resampling of the vertical profile. For my current purposes, any attributes of interest from these databases needs
to be linked to a point vector as an intermediary step towards being
rendered by voxels. In the specific case of categorical data, I am working with the data assumption that the attributes will be assigned to a point vector located at the bottom of the interval. <br><br>Historically soil inventory profiles have usually been a bit sloppy with locating elevation absolutely. All of the depth measurements were recorded in relative terms to the surface. Would it be possible to deal with high resolution z coordinates in a manner that was relational in the same way that soil profiles are collected. The reason I ask is that I worry about the amount of data required to tile voxels has the potential to grow inordinately. 10 cm is a pretty rough vertical resolution for soils purposes, but if you have to populate voxels for a field area that has 100 meters of elevation it could get overwhelming. The other route I am seeing is to create a mask from a digital elevation model to constrain the region to voxels near the surface elevation. All of the workspaces I am developing as examples for this project are areas where I have lidar coverage to pin the depth intervals to a high resolution elevation datum. <br>
<br></div></div></div></div></div></div></blockquote><div><br></div><div>I have often wondered about the scale issue you bring up. 1cm precision in the vertical vs. 10m precision in the horizontal is often a good compromise for soils/landscapes in the western US. This would result in some pretty funny looking voxels-- more like waffles. A decent mask and tools for rapid development of a mask would be essential.</div>
<div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><div><div><div><div></div><div>Away from soils field I have found some interesting issues in the data practices. In the geotechnical boreholes the sampling intervals are not always continuous, and they are specific. Also the reason why I have put in a line vector in my process is that the vertical assumptions will not always be met by the data. It occurs to me that a future iteration of this module is going to want to use dynamic segmentation in order to render data from boreholes that are not vertical and are only as straight as the the borehole that is drilled. Also I hear that horizontal drilling is becoming a very big deal in the energy sector and I can only imagine that groundwater prospecting is going to follow. <br>
</div></div></div><br>Also during the project review period Hamish mentioned an interest in Seismic line interpolation. At the time I worried that a digression into applied geophysics might be a dangerous distraction but I have subsequently worked up a workflow for the processing of p-wave first arrivals. I am suppressing any thought of any signal that is not a first arrival, but I think that I can make it work within a day. I am going to the library this afternoon to look into this some more. <br>
<span><font color="#888888">
<br></font></span></div><span><font color="#888888"><div>Tim<br></div></font></span></div></div>
<br></blockquote><div><br></div><div>Again, glad to see someone working on this issue and always happy to offer insight from the soils/NRCS perspective.</div><div><br></div><div>Cheers,</div><div>Dylan</div><div><br></div>
<div>PS: I have cc-ed my "work" email address, as I don't always check my gmail account.</div><div><br></div><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
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