Drone Mapping – Business Models Revisited

I am currently attending the 2017 NSSGA/CONEXPO exposition.  One of the keynotes from the National Stone, Sand and Gravel Association (NSSGA) conference focused on the rate of change of technology in the mining industry and the scope of operations that are covered by these technologies.  Of course, one of the examples was the use of drones.  The gist of the discussion was that some of these technologies are in their formative stages; we do not yet fully appreciate the scope of operational affect they will have but to prosper, knowledge of these systems must be internalized.

One thing is very clear – frequent and repetitive mapping will be required to support the automated machinery that is now appearing on advanced sites.  You cannot program a haul truck for autonomous operations if you do not know the location of the road!  Complicating this issue is the fact that the road location changes nearly daily due to the operation itself.

This future trajectory says that mine site mapping will need to become an internal operation.  It will be impractical from both a logistics and cost perspective to outsource drone mapping services.  A second strong consideration is the rapidity with which drone technology is changing.  I think amortizing the cost of a drone over more than 12 months is just not realistic.

Drones are simply platforms for cameras and other sensors (for example, profilers, laser scanners and so forth).  A drone without a sensor is a fun toy to fly but it is not going to have much use in operations!  I am very excited about new platforms from commercial drone companies (mostly DJI).  These new drones include decent cameras in that they now incorporate larger sensors and hybrid shutters.  You can do a reasonable job of mapping with these yet still use them for inspection videos.

DJI Inspire

So I think what we are seeing is the beginning of the end of the purpose-built drone.  You will be able to purchase drones from DJI (and perhaps others) that are nearly a consumable.  You can use the same drone for inspections as you use for mapping.  This is a very important consideration since this greatly simplifies the training of users.

The bottom line here is this – we are seeing the beginning of drones as an everyday tool for mining, industry and construction.  The proper model is going to be internal control of not only flying the systems but also processing the data.  When you need a quick check of a pulley on a conveyor, you will want an internal staff member to quickly fly the inspection job and post the resultant video.  No need to have a third-party system or contractor involved.  It just complicates the flow and adds expense.  This is really the motivation behind our Bring Your Own Drone (BYOD) Mapping Kit.  It lets you use a low-cost drone such as the DJI Inspire to do serious mapping without a lot of complicated leasing or outsourced data processing arrangements.  It also allows you to use the same platform for inspection that you use for mapping.  Give us a call to see how well this solution will meet your specific needs.

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What Miners Want

I attended the Commercial UAV Expo in Las Vegas at the end of October.  I gave a talk entitled “Mine Site Mapping – One Year In.”  This talk was on our experiences with performing mine site mapping services with our AirGon Services group.   Our services group is primarily about Research and Development (R&D).  We use our engagements with mining companies to discover the products that they need, accuracy levels and, most of all, how to reliably create these products.  These experiences inform both the development of our technology (the MMK, Topolyst, Reckon, the BYOD Mapping Kit) but also help us develop best practices for both collection and processing.

As I prepared for this presentation, I reviewed the mine site mapping projects we have performed over the past several years to tabulate the products our customers have requested.  These turned out to be, in decreasing order of popularity:

  • Site Volumetrics with a priori base line data
  • Site Volumetrics with no prior data
  • Site contours (“topo”) – 2 foot interval
  • Site Contours – 1 foot interval
  • Time series volumetrics (“borrow pit”)

In every case, the customer desired a site orthophoto.  In fact, they usually want an ortho of the entire site with analytic products of a subsection of the mine site.

I thought in this month’s section, I would review these products from the acquisition and processing point of view.

 Volumetrics with baseline data

I have written a few articles about injecting a priori data into a mapping project.  This is the situation where, at some time in the past, the customer has done a site survey and wants to use these data as the bottom surface of stockpiles.  Their primary desire here is for consistency from inventory to inventory.

An example of this, a large limestone quarry that we fly, is shown in Figure 1.  Here baseline data as well as a reclaim tunnel model have been provided to us as a DWG data set.  The illustration of Figure 1 shows these data being used by Topolyst to create a 3D base surface.

 

Figure 1:  Bottom Data with reclaim tunnel model

Figure 1: Bottom Data with reclaim tunnel model

The primary challenge that we have when receiving a priori data is the accuracy of the data.  We often find that these data were obtained by traditional stereo photogrammetric collection techniques so we do not have a point cloud from which to assess accuracy.  Now, done properly, stereo photogrammetry produces survey grade data.  Unfortunately, much of this a priori data was collected with the surface obstructed by existing stockpiles; in other words, it was not a stockpile free base data mapping.  This means that the stereo compiler had to estimate locations under the existing data.  We find that in most cases, these estimations are simply linear interpolations from one side of the obscured area to the other.  We often find these bottom models extending above the current surface.  It is difficult to tell if the data were incorrectly modeled or if the ground has actually changed from the time the baseline data were collected.

A second big challenge we have with these data are a lack of knowledge by the provider as to the exact datum to which the data are referenced.  We are often concerned with elevation differences of just a few centimeters.  The Geoid model really matters when you are approach survey leveling accuracy goals.  We have found, on more than one occasion, a priori data with an incorrect vertical model.  This usually occurs (at least in the USA) as a result of using the incorrect NAD83 to WGS84 transformation.

Over the past year, we have added a lot of refinements to how Topolyst handles this a priori data.  Those of you who do LIDAR or photogrammetric processing will immediately recognize this as the problem of introducing “breaklines” and “mass points” into a model.  LP360 (Topolyst is just a variant of LP360) has always been a very strong product in terms of breakline modeling.  We have added a few features in this area to improve the modeling as it typically applies in UAS mapping.  We are now at the point where we really do not have any software issues with this sort of modeling but the interpretation problems will always remain.

This type of modeling requires:

  • Direct geopositioning (RTK/PPK) on the drone
  • Multiple surveyed check points on the site for data validation
  • Strong modeling tools such as Topolyst
  • A conference or two with the customer to understand the models
  • A lot of patience when defining stockpiles

Volumes with no a priori data

Here the customer is interested only in the volumes of the piles, without regard to location.  The deliverable is generally a spreadsheet with volume, material type, density and tonnage.  Of course, our customer deliveries are via our cloud data platform, Reckon, so we want the toes to be correctly georeferenced.

If you leave out the correct georeferencing (meaning you compute the volume of the pile but do not necessarily try to align it with an existing map), you have the sort of processing offered by a myriad of web-based solutions such as Kespry.  Under this business model, you typically upload the raw drone images which have been georeferenced by the navigation grade GNSS for x, y and the drone barometric altimeter for elevation.  This typically provides horizontal accuracy on the order of several meters and vertical accuracies at about 5 meters.  So long as the camera is properly calibrated, this methodology leads to volumetric accuracies that are accurate to within about 5%.

We never do these projects without some check points.  These are surveyed image identifiable points that we use to check horizontal and vertical accuracy.

The biggest issues we have encountered with this type of project is the definition of the stockpile toe – it is somewhere between comingled piles, it traces along an embankment such as the pit, the stockpile is in a containment bin and so forth.   There requires a lot of careful toe editing in a three dimensional visualization environment such as Topolyst.

We never have issues with accuracy because we always fly with a direct geopositioning system.  For our MMK, it is a Post-Process Kinematic, PPK, GNSS system.  For the senseFly eBee, it is an onboard RTK system.  We always lay out some checkpoints for project verification.

A very clean mine site with stockpiles sitting on a surface is nearly non-existent (except in our dreams).  While you sometimes encounter sites where you can just manually draw a toe, these sites are nearly always at inventory transfer locations, not working mines.  In fact, of all the mine sites we have surveyed, we have encountered only one “groomed” site (see Figure 2).  Even at this site, the upper left and lower right piles required some disambiguation (wow, that’s a big word!) work to separate the pile edge from encroaching vegetation.

Figure 2: A "groomed" inventory site

Figure 2: A “groomed” inventory site

 Site Contours (“topo”)

A surprising number of customers want contours.  As you know, these are elevation isolines at a particular interval.  Most customer want either 2 foot or 1 foot contour intervals.  These data, in DXF or DWG format, are used as input to mine planning software.  I find this a bit odd since I would think by now that this downstream software would directly ingest a LAS point cloud or at least an elevation model.

Contours are always absolutely referenced to a datum (a “Network”).  This can be a local plant datum or, much more commonly, a mapping horizontal and vertical datum such as a state plane coordinate system for horizontal and NAVD88 with a specific geoid model for vertical (at least in the United States).

You can tie to the datums using either direct geopositioning with onboard RTK/PPK or you can use dense ground control points.  I personally would never collect data that must be tied to a datum without having a few image identifiable checkpoints.  Unfortunately, this means that you will need at least an RTK rover in you equipment kit.

A good rule of thumb for contours is that the accuracy of the elevation data should be at least three times the accuracy of the desired contour interval.  This says if you are going to produce 1 foot (30 cm) contours, you need 4” (10 cm) of vertical accuracy relative to the vertical datum.  When you measure your checkpoints, don’t forget to propagate the error of the base station location (which you might be deriving from an OPUS solution).

Preparing a surface for contour generation is perhaps the most tedious of mine site mapping work.  It is generally the only site mapping you will do that requires full classification of ground points (the source for the contour construction).  An example of 2 foot contours within a mine site is shown in Figure 3.

Figure 3:  An example of 2' contours

Figure 3: An example of 2′ contours

Sites with a high degree of vegetation in areas where the customer wants contour lines will have to be collected with either manual RTK profiling (very tedious!) or with a LIDAR system.  You simply cannot get ground points with image-based Structure from Motion (SfM).  No surprise here – this is why LIDAR was adopted for mapping!

If the customer does not want to pay for LIDAR or manual RTK collection, the vegetated areas should be circumscribed with “low confidence” polygons.  You can either exclude the contouring completely from these areas or classify the interior to vegetation and let the exterior contours just pass though the region.  In any event, the customer must be aware that the data are quite inaccurate in these regions.

The SfM algorithm gets quite “confused” in areas with overhead “noise” such as conveyors and vegetation.  This confusion (actually correlation errors) typically manifests as very low points.  You will need to find and clean these points prior to contour generation.

Conclusions

Product generation for UAS mapping requires a lot of front-end planning.  This planning needs to be product-driven.   If you customer (you, yourself, perhaps) needs only volumes with no tie of the toes to a datum, you can get away with no control so long as some other information such as camera calibration and flying height are correct.  By the way, we recommend never collecting this way since you are precluded from doing any meaningful time series analysis.

On the other hand, most meaningful data (that is, you can quantify the accuracy relative to a datum) will require a very careful control strategy as well as a rigorous processing workflow with the right tools (meaning Topolyst, of course!).  No matter what geopositioning strategy you employ, you should always have some independent methods for verifying accuracy.

If all of this seems a bit daunting, you can get assistance from us.  Remember, our services group is really our R&D lab.  Our real goal is to sell technology to owner/operators and production companies.  No matter what drone you are using, you can always avail of our consulting services.  We have gained a lot of experience over the past few years, mostly by first doing the wrong thing!  Save yourself this time and money by engaging with us!

 

 

 

AirGon Happenings

I am pleased to announce that AirGon’s request for amendment to its Section 333 waiver for flying commercial small Unmanned Aerial Systems (sUAS) was approved in April.  Our amendment adds all current and future 333 approved aircraft to our 333.  AirGon can now fly any sUAS that has ever been approved by the FAA as well as all future approved systems.  This list currently contains 1,150 different sUAS (AirGon’s own AV-900 is number 207 on the list).  This provides us a lot of flexibility in working with clients; for example, in situations where a glider sUAS is more efficient than a rotor craft.

The FAA has also recently streamlined the process of obtaining an N number for a sUAS.  Prior to the change, a paper process that required several months was the only option.  Now an online system is available, greatly simplifying this procedure.  Note that this is not the new online registration system for hobby drones but rather the system used for obtaining an N number for a manned aircraft (if you are confused, join the club!).  Combined with our new 333 amendment, we can now get a new aircraft legally operating within days.

We continue to do a lot of work to optimize the accuracy of point clouds derived from dense image matching (DIM).  DIM are the data of choice for sUAS mapping since they can be generated from low cost prosumer cameras using standard application software such as Pix4D Mapper or PhotoScan.  The question always remains as to how good these data really are.

It has taken us a lot of experimentation and analysis but we think we have fleshed out a procedure for assuring good absolute vertical accuracy.  It involves the use of Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS) positioning on the sUAS, a local base station that we tie into the national Continuously Operating Reference Station (CORS) network and the National Geodetic Survey’s Online Positioning User Service (OPUS) to “anchor” the project to the network.  We have also discovered that high vertical accuracy cannot be obtained without camera calibration.  We typically use an in situ process for calibration.  We have flown many dozens of sites (primarily mining), giving us a rich set of test data.

I cannot over emphasize how critical network vertical accuracy is.  Most customers want elevation maps of their sites.  These are usually delivered as contour vector files.  As we all know, a 1 foot contour requires vertical accuracy of 1/3 of a foot.  This is a very tight requirement!  A three inch vertical bias error over an acre is an error of about 400 cubic yards – this is significant.

We see a lot of drone companies processing site data with no control and no RTK/PPK.  While, with the introduction of scale into the model (many companies do not even do this), one might obtain reasonable difference computations (such as volumes), the network accuracy is very poor (obtained from the airborne navigation grade GNSS only) and hence the data are of limited use.  We have discovered that these techniques (where no control and/or RTK/PPK is used) can result in the vertical scale being incorrectly computed.  This means that even differential measurements are not accurate.  Why spend all of the money to collect these data if they are of unknown accuracy?

A more difficult area that we have studied over the past several years is what I refer to as “conformance.”  That is, how well does the DIM actually fit the object being imaged?  DIM processing software (again, such as Pix4D and PhotoScan) do a miraculous job correlating a 3D surface model from highly redundant imagery using the general class of algorithm called Structure from Motion (SfM).  In addition to the obvious areas where SfM fails (deep shadow, thin linear objects such as poles and wires), a lot of subtle errors occur due to the filtering that is performed by the SfM post-extraction algorithms.  These filtering algorithms are designed to remove noise from the surface model.  Unfortunately, any filtering will also remove true signal, distorting the surface model.

We are working with several of our mining customers to quantify these errors and, once these errors are characterized, to develop best practices to minimize or at least recognize when and where they occur.  An example of an analysis is shown in Figure 1.  Here we are analyzing a small pile (roughly outlined in orange) of very coarse aggregates with a volume of about 340 cubic yards.  This site was flown with a very high end manned aircraft LIDAR system and with AirGon’s AV-900 equipped with our RTK system.  The DIM was created using Agisoft PhotoScan.  We obtained excellent accuracy as determined by a number of signalized (meaning ground targets visible in the imagery) control and supplemental topo only shots.  We used in situ calibration to calibrate the camera (a Sony NEX-5 with a 16 mm pancake lens).

As can be seen in Figure 1, we created a series of cross sections over the test pile.  These cross sections were generated using the Cross Section Point Cloud Task (PCT) in LP360/Topolyst.  This tool drapes cross sections at a user specified interval, conflating the elevation value from the user specified point cloud.  We ran the task twice, conflating Z first from the LIDAR point cloud and then from the DIM.   In Figure 1 we have drawn a profile over one of the cross sections with the result visible in the profile view.  The red cross section is derived from the LIDAR and the green from the DIM.

Comparing LIDAR (red) to DIM (green)

Comparing LIDAR (red) to DIM (green)

Note that the DIM cross section (green) is considerably smoother than the LIDAR cross section (red).  This is caused by several factors:

  • The aggregate of this particular pile is very coarse with some rocks over 2 feet in diameter. This leaves a very undulating surface.  The LIDAR is fairly faithfully following this surface whereas the DIM is averaging over the surface.
  • The AV-900 flight was rather high and the data was collected with a 16 mm lens. This gave a ground sample distance (GSD) a little higher than is typical for this type project.
  • Due to the coarseness of the aggregate, significant pits appear between the rocks, creating deep shadows. SfM algorithms tend to blur in these regions, rendering the elevation less accurate than in areas of low shadow and good texture.

The impact of lower conformance is a function of both the material and the size of the stockpile (if stockpiles are what you are measuring).  For small piles with very coarse material (as is the case in this example) a volumetric difference between LIDAR and SfM can be as great as 20%.  On larger piles with finer aggregates, the conformance is significantly better.   For example, in this same test project, we observed less than 0.25% difference between LIDAR and the DIM on a pile of #5 gravel containing about 30,000 cubic yards.

There still remains the question of which is more accurate – the volume as computed from the LIDAR or the volume as computed from the DIM?  I think that if the LIDAR are collected with a post spacing ½ the diameter of the average rock, the LIDAR will be the most accurate (assuming that it is well calibrated and flown at very low altitude).   However, the DIM is certainly sufficiently accurate for the vast majority of aggregate volumetric work, so long as a very strict adherence to collection and processing best practices is followed.  For most high accuracy volumetric projects, manned LIDAR flights are prohibitively expensive.

We continue to do many experiments with local and network accuracy as well as methods to improve and quantify conformance.  I’ll report our results here and in other articles as we continue to build our knowledge base.

December 2015

Well, like everyone is saying, I cannot believe that 2015 is drawing to a close.  Where did the year go?  This will be a short note – I have to get some Christmas shopping done!

We finally released LP360 this past week.  Our early postponement was to squeeze new features into the products whereas the later delays were to ensure stability.  We have been using the products in our internal production processes for the past few months.  This has been a great experience in terms of fine tuning features and monitoring stability.

One of the things we have been focused on is production processes.  Of course, repeatable process is what the GeoCue workflow products are all about so this is not a new thing for us.  We have always appreciated that quality is most directly related to rigorously controlled processes, not to the heroics of individual production folks.  Now that we are doing a lot of field work, we are examining ways to improve this aspect of the process.  For example, the field work associated with acquiring mine site data with an sUAS is tricky.  It is not that the individual steps are particularly complicated, it is that there are a lot of steps that must be successfully accomplished in a specific order.  We are currently using a lot of checklists.  This is the minimum required to be successful.  How do we improve this process in harsh environments that often lack connectivity to the outside world?  No clear solutions yet but we are working on it!

We have also been working on simplifying our business structure.  We acquired QCoherent Software LLC (a Colorado-based company) in 2009.  Over time, we have moved all of the company to our headquarters in Huntsville, Alabama.  We are finally absorbing the corporate structure into GeoCue Group.  You will not notice any changes other than communications related to LP360 and LIDAR Server now being from GeoCue Group Inc.

We will soon be releasing Service Pack 4 for the GeoCue product set.  The next major release will be in 2016.  We are working on some simplifications to the product as well as better schemes for archiving products.  I think you will appreciate these changes.

Terrasolid is now offering a true 64 bit version for MicroStation CONNECT (the version of MicroStation that succeeds V8i).  Maintenance customers will have access to this new version of Terrasolid tools.  We do caution however, that this is still in the beta stage and is probably not sufficiently stable or feature complete to introduce into production.   We estimate that this new version will be production ready by the end of Q1 of 2016.

During this past year we have learned an incredible amount about how to design sUAS for mapping as well as the tools and processes needed to create products.  This overall workflow is fundamentally changing small area mapping but it is not easy to achieve accurate and repeatable results.  We now have come to realize that mine site mapping requires control 100% of the time and establishing this in dense image matching workflows is not at all straightforward.  I think this is good news for the professionals out there providing these services.  In the area of metric mapping, you will not be easily displaced by someone buying an inexpensive drone and a point cloud generation software application!

All of us here at GeoCue Group wish you a very relaxing holiday season and the very best of success in 2016!

November 2015

First of all, I have to apologize for us not releasing LP360 at the end of October as I promised in the last issue! We needed to add a feature to LP360 to assist with very dense data sets. This new “Classify by Statistics” point cloud task can be used for a variety of functions, among them data thinning. We also took the time to tune a number of different performance bottlenecks, including clipping contours to a project boundary.

We have entered the services business in a small way. We have encountered a number of mine operators who want to collect maps and volumes of their sites using small unmanned aerial systems (sUAS) but they are not yet ready to internalize the process. To assist with this transition, we now offer flying and data processing services to these customers. We do the bulk of this production in LP360 with a bit in our GeoCue workflow products.

One thing this foray into production is teaching us is the value of removing “clicks” from the production process! We are usually so focused on adding advanced features to our products that we overlook the simple things that can greatly improve the speed of a workflow. For example, we changed the destination class selector in the profile classification tool in LP360 to remember the destination class. This is a simple change that took a developer about 1 hour to incorporate. It now saves a data production technician many clicks in the classification process. You can be assured that we will have a renewed focus on basic productivity going forward!

We are in the midst of product planning for 2016. I think we have some pretty exciting developments in the pipeline. I will highlight a few here; you will be hearing details of these as 2016 rolls out.

On the GeoCue workflow software front, we intend to focus some energy on simplifying the product. When we first brought GeoCue to the market in 2004 (we started building the product in 2003), the average production shop employed technicians who were accustomed to “tool box” software with very complex features that a user could stitch together into a workflow that suited their particular needs (sound a lot like the ArcGIS desktop products, right?). Now we find many organizations who are constructing workflows that they would like to be more “black box” and that just work out of the box. This is not unusual to see this occur as a technology such as LIDAR matures.

Our cloud-hosted products, LIDAR Server and Reckon, will see major capability additions in 2016. LIDAR Server will continue to be the premiere solution for managing and delivering LIDAR data in point cloud format whereas Reckon is the life cycle management and storage environment for mine site sUAS mapping. Already we have added the ability for Reckon to serve as a WMS server for clients such as ArcMap and Autodesk. This allows a mine site engineer to bring up to date site imagery and vectors into these environments without the need to take physical delivery of this voluminous data.

Reckon is our first “subscription-only” product. Hosted in Amazon Web Services, this data portal is evolving into a system not only for reviewing mine site mapping by site and mission date but also for annotating stockpiles and planning the next mission. The huge advantage of this over more traditional means, such as trying to use Google Earth imagery, is that the mine engineer can use the most recent view of the mine (for example, last month’s flight). This is nearly a requirement since the topology of these sites are so dynamic.

We are also modernizing the display architecture of LP360 to take advantage of advanced features in workstations and laptop video hardware. Advanced capabilities such as hardware rendering that were once found only in high end video cards are now common place, even in lower end laptops. The 2016 software base will “discover” graphics features and use whatever hardware capabilities found in the discovery process. We will, of course, support fallback to software algorithms for those machines lacking advanced features.

2015 will be the final release year for GeoCue Group software products to support Windows XP as well as 32 bit operating systems (other than our 32 bit LP360 extension for ArcMap). The “experimental” and final releases of 2016 will support Windows 7 and beyond, in 64 bit only. It has been quite some time since Microsoft ended support for Windows XP. We no longer receive development support for XP in Microsoft Visual Studio (our development environment) and thus must retire support for this venerable operating system.   Many other vendors such as ESRI have already ended support for XP so those still on this system should plan accordingly.

For those of you in the United States, we wish you a very enjoyable Thanksgiving holiday!

Best Regards,

Lewis

Development, Windows 10, and EXP LP360 2015.1

We are entering the hottest and most humid part of the year here in Alabama so, like January, this is a good time to stay indoors and do things like system design!

We do a lot of system engineering and development work here at GeoCue. This ranges anywhere from customizations of our GeoCue workflow tools to new (“green field”) developments. I have noticed that more and more frequently we consider cloud hosted environments such as Microsoft Azure and Amazon Web Services (AWS) as our solution platform. Besides fractional scaling (add more when you need it, remove it when no longer needed and pay for only what you use), we really like the data storage options. Prohibitively expensive just a few years ago, you can now consider archiving all of your production data in the cloud. For example AWS offers its Glacier archival storage for less than $125 per Terabyte per year. There is just no way to do this on premise with the level of assurance of no data loss that you can get with AWS. At any rate, cloud deployed solutions make more and more sense as this paradigm matures. It is rather ironic since when my great granddaddy started in this business he was renting access to a remote time share system. The more things change, the more they stay the same!

I just upgraded my workstation-class laptop to Windows 10. Since I was moving from Windows 8.1, this has been a positive experience. I have not yet had a lot of experience with the various capabilities so the jury remains out on which is better for workstation (no Microsoft, we don’t do image and LIDAR processing on tablet PCs !!) – Windows 7 or Windows 10? There is a detailed story of my installation experience in this newsletter.

If you are an LP360 customer on maintenance (thank you very much!), you may have already installed our 2015.1 EXP release (yes, it finally went out the door!). The purpose of the Experimental release is to provide you with an early look at some of the features we are adding to the official release. Examples in the current EXP release include three new major tools:

  • Live View – A completely redesigned, real time interface for filtering the display
  • A Ground Cleaner Point Cloud Task (PCT) – this new PCT (available at the Standard level) is a tool that allows you to very rapidly clean up areas of ground classification that are incomplete (a common problem in delivered LIDAR data)
  • An Automatic Stockpile Toe Extractor PCT – This is a tool still in beta form. It allows you to automatically create polygons at the base of a stockpile by simply selecting a point on the pile. This tool really speeds up volumetric analysis

If you are not currently on maintenance, contact Ashlee Hornbuckle at ahornbuckle@lp360.com and she can assist you with returning to the program.

We will soon be moving our licensing to a cloud-hosted solution. This will make self-service of common licensing operations possible. We’ll first move LP360 and then look at our other products. This will take a bit since we have to do this development in-house.

OK, enough said! I have to get back to work! Have a great remainder of the summer!

Best Regards,

Lewis

LP360 Testing, Metric Mapping Kits and a New LIDAR Server

I spent the week of the Fourth of July at my beautiful retreat on the lovely Tennessee River, ostensibly on holiday. In reality, I was sitting with my laptop at the kitchen table writing magazine articles. I am not complaining though – the view is fabulous!

I was also very busy delaying our experimental release of LP360. I did a complete run-through of our new Live View display filter, sending multiple suggestions for tweaks to the development crew and testing out their new builds. On some days we cycled three builds! This is a real advantage of working from Casa Rio. If I were at the office, they would probably knock me in the head! The effort will be worthwhile – this has turned out to be a very nice tool for quickly modifying the display of point cloud data.

I am pleased to report that sales of our Metric Mapping Kit are beginning to take off (pun intended). The AV-900 MMK is a bundle of all of the hardware and software needed to do local area metric mapping and volumetric analysis. We have now collected test data over a wide variety of sites with much effort expended on analyzing metric accuracy as a function of variable parameters such as control, RTK, stockpile toe definition and so forth. The results are truly stunning. sUAS technology will be a paradigm shift for this type of analysis.

I am also pleased to announce (there will be a press release in the next week or so) an option for filing FAA 333 exemptions for the MMK. If you purchase an AV-900 MMK, we (well, actually our attorney) will file your complete FAA 333 petition for a flat rate of US $1,295.

Speaking of stockpiles, the EXP release of LP360 (I promise we will release this by 15 July!) has a new point cloud task (PCT) for automatically digitizing the “toe” of a “clean” stockpile. Simply click a point on a pile and – voilà – a 3D stockpile toe! This tool is showing great potential and will be refined as we work on the final 2015.1 release. Our goal is to make stockpile collection as simple and repeatable as is possible. This function will be available in the Windows (“standalone”) release of the Standard/sUAS level of LP360 at EXP but will be in the ArcGIS extension by the time we deliver the final 2015.1 release.

Have a look at the latest iteration of LIDAR Server. You can view demonstration data sets by visiting www.lidarserver.com. We have replaced the legacy Silverlight client interface with an all new JavaScript browser. LIDAR Server is a great technology for hosting county-wide LIDAR data deliveries, making them available to constituents for viewing and ad hoc deliveries. For example, if a county engineer needs LIDAR data in the vicinity of a road intersection, she can just digitize an area of interest in the LIDAR Server client and download the dynamically created LIDAR data set to her workstation. We are doing a lot of work on LIDAR Server so there will be more to come!

Speaking of servers, our Reckon volumetric results management system has reached what might be called “version 1.0” ready for use. Reckon is a hosted service, running in Amazon Web Services (AWS). It is aimed at both owner-operators of surface mines as well as service providers. Right now you can experiment with Reckon by contacting us for an account. By the end of this month, we will have a new Reckon web site up with a live, on-line demo; stay tuned!

Keep enjoying your summer – see you in August!

Lewis Graham, CTO GeoCue Group

3DEP, LP360 Toolbox and AirGon

I am looking for the month of May – it seems to have disappeared without a trace!

We recently visited with the Tennessee Office of Information Research (OIR) in beautiful Nashville, Tennessee. The OIR is the coordinating state agency for a USGS 3DEP LIDAR (3 acronyms in a row – not quite a record!) acquisition project. Under this program, the state of Tennessee will be flown at Quality Level 2 (2 points per square meter) over a four year period. The initial collection (slated for this fall) will encompass some 11,500 square miles, covering 27 counties.

3DEP is an excellent opportunity for state and local government agencies to pool their financial (and often technical) resources to obtain point cloud data. By spreading the cost across a spectrum of stakeholders, a surprisingly large amount of data collection can be accomplished.

Our discussions with the OIR led naturally to a conversation about how LIDAR data are used in GIS and engineering departments. We covered the usual suspects such as flood plain analysis, basic 3D visualization, site planning and so forth. By the end of the conversation, I was convinced (as usual) that every single state and local government GIS workstation should have access to a current image and current 3D (e.g. LIDAR point cloud in LAS format) backdrops. Why would anyone find it acceptable to be without a cross-sectional view of their municipal data on an ad hoc basis? Mainly because they have never had this level of information available. You never miss what you have never had!

When we returned to the office, we decided to put together, once and for all, a package of material for folks who are either contemplating acquiring LIDAR data or those who have access to LIDAR data. We will develop use cases and return on investment information for the range of applications that make sense for these data. If you have some novel ideas and particularly case studies, please work with us. Obviously we want to sell more software but we believe a rising tide lifts all boats. We need to get the tide (meaning the understanding and effective use of LIDAR data) rising first!

Speaking of software, we hope to have our experimental release (EXP) of LP360 available for download by the end of this month (June). The developers are doing fine. It is me who always throws a wrench in the delivery schedule – “let’s get return selection added to the new Live View dialog before we release…” Speaking of Live View, this is a new dynamic filter in LP360 that lets you change class, return and flag filtering on the fly. You are really going to like this new feature!

While we try to make features in our tools easy to use, the LIDAR tools on the market still tend to be toolbox oriented rather than workflow specific. For this reason, it is very important to participate in training if you hope to realize a maximum return on your investment. We offer a range of training (and consulting) from web based to on-site. In addition, we have our Huntsville-based LP360 training coming up in the fall.

On the AirGon side of things, we have been talking to a lot of potential clients who can make immediate use of small Unmanned Aerial Systems (sUAS) mapping. We offer a complete helicopter-based metric mapping kit in the AV-900 MMK. This is garnering a lot of interest since it provides a turn-key solution of hardware, software and training for doing jobs that have an immediate high return on investment such as stockpile volumetric analysis. However, we also offer just the piece parts for those who wish to assemble their own system. For example, if you have decided on a small wing type sUAS such as the eBee from SenseFly, LP360 for sUAS is still your best option for extracting volumetrics (anyone who has tried to do a multi-pile site using the point cloud generation software shipped with these systems will readily agree!). In addition, AirGon Reckon is the best product in the market for hosting and delivering mine site orthos and volumetric reports. By hosting our volumetrics delivery system in Amazon Web Services, we relieve you the need to worry about data delivery to multiple offices, data backup and security.

Summer promises to fly by just as quickly as the spring. We are attending a number of conferences such as the ESRI meeting and the Transportation Research Board AFB-80 summer meeting. If you are attending one of these, please look us up. See you in July!

Drones, Metric Mapping and RTK

We have been very busy this first third of 2015 with software development (as we always are).  The thing about software is that it is never static.  It is either undergoing new additions or entering the end of life phase.  We have had a very big focus on ensuring that our products are optimized for LAS 1.4 support as this is the new requirement of the USGS.  Additionally, we like to use LAS 1.4 in our mine site workflows since it supports a few nice capabilities that were not in LAS 1.3.

This is definitely the year of the drone.  Every major geospatial hardware firm has announced a drone system for remote sensing (some for metric mapping).  While the USA is inching along toward some usable drone rules, other countries have clear rules in effect and drone mapping is becoming a standard survey/mapping tool.

We are garnering a very high interest in AirGon’s Metric Mapping Kit (MMK).  This solution provides everything you need to do uncontrolled mapping projects using a small Unmanned Aerial System (sUAS) except a processing laptop computer.  Add in your own surveyed control points to reach survey grade accuracy.

Speaking of the Metric Mapping Kit, we will be hosting a AV-900 MMK workshop in Toronto, Canada on June 11th and 12th.  Thanks to Jim Giordano, we will be presenting live flight demonstrations at VicDom Sand & Gravel as well as an in-depth look at mission planning and post-collection data processing.  Our focus will be on drone-collected volumetrics. Personal protection equipment (steel toed boots, hardhat, safety vest and safety glasses) are required.  Remember that a passport is required for travel between the USA and Canada.  Space is extremely limited so sign up early!

We have been (in a joint project with Applanix, a Trimble Company) researching the use of Post-Processed Kinematic (often erroneously called Real Time Kinematic, RTK) control solutions.  Obviously everyone flying a sUAS for metric mapping purposes would like to dispense with the tedium of deploying ground control.  We will publish the results of our efforts as a white paper when the work is complete.  My goal is a recipe, if you will, of the methods that are appropriate for a given desired accuracy level.

We will be posting an experimental (EXP) release of LP360 (all license levels) within the next few weeks.  Those of you on software maintenance will be able to download this release via the “Check for Updates” option under LP360 Help.  There is a separate article in this newsletter that provides a highlight of the new features.

Till June – Best Regards,

Lewis

GeoCue Group News – May 2015

sUAS – Where will this business go?

The small Unmanned Aerial Systems (sUAS) business is very appealing. For less than US $20,000, you can outfit a complete system for collecting aerial imagery and processing the data into an array of high quality mapping product.

But who will roll out these new low cost mapping systems?  Will it be the major airborne acquisition companies?  Perhaps, but with a business model predicated on large collects, does this fit?  Will it be the owners of the sites that require mapping such as quarry owners, land developers, coal fired power plants?  Or will it be professional land surveyors who offer sUAS mapping as another tool in their toolbox?

In my mind, the professional surveyor is best equipped to roll out this new business tool.  The PS is already tuned to a business model of travelling to small sites, collecting  data, processing results and consulting with the client.  The sUAS will provide a new tool that will allow the PS to offer a broader range of more accurate services to the client base.  For example, rather that delivering estimated elevation models based on a few RTK points, she can now deliver very dense point cloud derived models based on dense image matching.

Perhaps the most exciting new business opportunity is the rapid collection of accurate volumetric data.  Today this is done either by manned aerial mapping or by ground based techniques.  Ground based techniques are very problematic for many situations since accurate data collection of complex or tall stockpiles is very difficult.  Manned airborne methods work extremely well but are prohibitively expensive for high frequency monitoring (even quarterly monitoring is not practical except for the most valuable of stockpiles).  Enter the sUAS.  A flight of 20 minutes can provide the base data necessary for very detailed volumetric computations over a typical 1 square kilometer area.  In fact, the entire process, from mission planning to client deliverable can be performed in less that one day.

The sUAS is upon.  Enterprising folks will figure out very quickly how to produce professional products at a profit.

(Read the GeoConnexion article describing our experience of putting together an sUAS system.)