The data following LP360 for sUAS’s automatic stockpile extraction are shown in Figure 2. Note the toe in the Map and 3D views as well as the automatic classification of the portion of the conveyor within the toe. This is an extremely powerful tool available in in LP360 Advanced that reduces the work of collecting stockpile volumes significantly. Our initial release of LP360 for sUAS also includes a very powerful collection of 3D feature editing tools that make quick work of manually digitizing toes or cleaning up toes in difficult locations (for example, along pit walls) following automatic extraction.
We have found, from completing many stockpile surveys, that correctly defining the toe is just the beginning! Mine site operators are keenly interested in consistency. For example, suppose a stockpile is measured on 5 January to have a volume of 1,000 yards3. The plant manager sells 500 yards3 from this pile during the period up to the next survey. She also estimates that 1,000 yards3 were added to the pile. The next survey should indicate a volume close to 1,500 yards3. If it does not, the person measuring the volume is the first suspect!
What are the causes of these discrepancies? The first is, of course, poor estimation. It is much more difficult to accurately estimate the volume of a pile by “eyeball” than one might guess. However, we have found the primary culprit to be the definition of the base of the stockpile.
Many mine sites keep a priori survey data that represent the terrain prior to placing any stockpiles (“baseline data” or simply baselines). Nearly all of the baseline data provided to us has been stereographically collected from a manned aerial survey. An example is shown in Figure 3. The magenta points are 3D “mass points” that were derived from a conventional photogrammetric stereo model.
The question arises as to how to consistently employ these baselines? There several approaches that one can take:
The third method probably gives the most consistent change of volume record from survey to survey but is it the most technically correct? This method assumes that all of the material from the toe to the baseline (recall that the baseline is actually under the surface on which the toe lies) could be extracted and used/sold. This is usually not the case.
As mappers of data, it is important that we advise mine site operators of the advantages and disadvantages of the various methods but, at the end of the day, produce the data according to the customer’s instructions.
Topolyst supports all of the aforementioned techniques for computing volumes (as well as a few others). For example, the hillshade of Figure 4 is a surface model constructed solely from photogrammetric mass points. Topolyst has the ability to dynamically use these data as the base where computing volumetrics. Topolyst also has the ability to generate a LAS file from point, polyline and polygon feature data. This is extremely useful since this “baseline” LAS can be used in a wide variety of analysis scenarios.
The features we are adding to Topolyst are being driven by our customer needs, our own needs within our analytic services group and by our research and development efforts aimed at process improvement. I very definitely welcome your feedback on current and needed features in this great product.