Any time a new technology – whether hardware or software makes its way onto the market and into our tool box, we are always quick to determine what it does and how it works. We take our new shiny toy around and shop it to our clients and tell them all the great things that it does how it will save them money, help them do something great or change the game. Equally (if not even more so) important, we should also know the limitations of our tools a common mis-step.
By knowing the limitations we dont oversell/misrepresent our new toys capabilities, or mislead our customer. In the case of Mobile LiDAR we can mitigate system limitations by effective augmentation of the collection methodology, or by supplementing collections with traditional surveying (or other means) to meet project requirements or expectations. Clients will respect us more when we are truthful about what we can, and cannot deliver.
The Manhole Example
Since placing our Mobile LiDAR system into service over a year and a half ago, Ive given countless presentations. Without fail, Im consistently asked the same question: How do we get invert elevations in manholes? Believe it or not, although Mobile LiDAR is an impressive technology, obtaining manhole inverts still requires removing the cover. Sure, you could pull every lid on a given route and drive that minefield with a LiDAR system, but I dont think anyones that irresponsible with crew and public safety (or have a big enough insurance rider) to propose that solution.
This example, albeit perhaps a little extreme, goes to the notion and in some cases the fear that Mobile LiDAR will someday replace traditional surveying, or that it is capable of handling every survey application. The truth is that Mobile LiDAR is simply another tool at the disposal of the surveying, engineering and GIS professionals.
What about Grass?
Perhaps the second most common question is how do we manage grassy surfaces in developing a bare earth digital elevation model (DEM), cross-sections, slopes, contours and other volumetric analysis. Since the premise of LiDAR requires line of sight to the object being measured ideally the ground any impediment is going to cause a challenge whether it is an artificial or a natural obstacle.
The accuracies we are attempting to achieve on a given Mobile LiDAR project, often far less than 0.1, requires more stringent analysis than other remote sensing techniques. Effective application of various and well-designed algorithms will allow you to successfully model a bare earth surface for areas having shorter grass, but dense ground vegetation can limit ones ability to accurately model the ground surface. By strategically utilizing GPS or traditional surveying techniques to acquire check points throughout the collection, we provide a means to validate our processing techniques, and overall data accuracy.
Living in Louisiana Im all too aware of our levee network. You can quickly differentiate Federal and non-Federal levees by their maintenance. Some local Federal levees are putting-green smooth, with bike trails or parks. The non-Federal levees have such dense vegetation growing on them they look like a developing rain forest. Knowing your systems limitations, accuracy requirements, and your clients expectations, are all needed in order to develop an effective, appropriate solution.
As with aerial LiDAR and photogrammetric applications, obscured features or regions present an additional challenge for Mobile LiDAR. I instruct our operators that if you cant see it, the system isnt measuring it. Often this premise yields an in-field augment to the collection, but sometimes these blind spots are unavoidable.
For example, in an urban environment, parallel parked cars will prevent complete coverage of the curb, gutter and features immediately behind the cars. Since augmenting the collection by driving on the sidewalk is likely not permissible, other field collection methodologies must be employed.
Educate yourself and your clients to your systems limitations. Knowing how to adequately compensate for those limitations forms the foundation for developing trust, a realistic project scope, a sound collection methodology, and ultimately project success.