AirGon Happenings - September 2016
Published On: September 17, 2016
This has been a very busy time for our AirGon subsidiary. While our primary focus is delivering hardware and software tools for high accuracy drone mapping, we also provide a limited amount of services. These services have been extremely helpful in providing a test bed for our positioning and processing tools. We continue to test and provide feedback to our LP360 for sUAS/Topolyst software development group regarding tools for improving the overall workflow experience. We run in to all sorts of complex modeling situations and we try to assess each in terms of tools that would ease and/or improve the workflows. For example, you will see a new tool to extract 3D vertices from line work in the latest EXP release of Topolyst/ LP360 for sUAS (standalone). This tool has been added to assist with modeling Low Confidence Areas (LCA) common to point clouds derived from Structure from Motion (SfM) algorithms. Another recent edition to LP360 for sUAS/Topolyst (all versions) is a new contour smoothing algorithm. This algorithm is designed to address the problems of meandering contours in areas of small vertical change (the meanderings are caused by either surface or algorithm noise). You will find that this new tool greatly enhances the appearance of contours in these problem areas. A typical meandering contour is depicted inFigure 1.
Figure 1: A typical meandering contour
This same map area after processing through the new smoothing algorithm is shown in Figure 2 - a dramatic improvement! Our algorithm works in model space (the model on which the contours are based) and hence is guaranteed not to introduce topology errors such as contour crossings.
Figure 2: Contour Processed through LP360 smoothing algorithm
We have been doing a lot of experiments lately with very low cost drones and cameras (for example, the Inspire Pro) as to their suitability for volumetric mapping. The results so far are mixed. We have discovered that, when using no control (an approach often used by folks not well versed in survey grade mapping) that an error in the a priori heights fed into SfM software will result in significant scale errors. These scale errors are not immediately evident since all of the data look terrific! I hope to be publishing a report on this within the next 60 days.
We did our first flights under the new Part 107 rules. We were collecting data near an airport in Class G airspace (something we could not do under the old Section 333 waiver without a special COA). We always carefully monitor air traffic via a VHF radio. At one point we heard a pilot declare "I see a drone down there over the mine site!" This is perfectly OK under Part 107 but takes a bit to get used to!
We are concluding that if you need point clouds from imagery (dense image matching, DIM or Structure from Motion, SfM) to meet the network accuracy requirements for high grade topographic mapping (such as 1 foot contours) you are going to have to use either RTK or PPK on your flight platform. Even with fairly dense ground control, we are not seeing the accuracy levels we need without RTK/PPK (and we have tried this with different systems and cameras).
We are considering a special training session later this year on drone data workflow processing using PhotoScan/Pix4D and Topolyst. We also may work with our local flight center to combine this with a Remote Pilot certification training/testing session. Drop us a line if you are interested in this.