So, I have been working with the guys to keep my feet wet with LiDAR data editing so that I understand more about what it takes to prepare the LiDAR surface for delivery to the client or for an ortho surface. I got my share of data and headed off to edit my surface…
Sounds pretty easy, right? Well, it actually is as long as you know what to look for. Our data for this project had a lot of low points in it – due mostly to the fact that we are shooting down stormwater grates in neighborhoods. This creates low points in the data that is not indicative of the true terrain. We usually filter these out using our filtering algorithms, but sometimes these points still exist in the data and need to be edited out.
The first way to identify a low point is to create a TIN of the surface. If there are low points, the TIN will be dragged down by the surface and there will be a gaping hole in the surface. Another way to identify these holes is to look at the color palette of the scene and if it does not have the usual distribution of colors – Red to Purple – there is a low point somewhere in the scene.
Low Point in TIN Surface
We can also see the low point using the “Profile” view – it can be seen below the surface.
Low Points Below the Filtered Surface
These points can be re-classified and removed from the Ground Classification and placed into the “Low Point / Noise” Classification and then the surface is modified. Note the better distribution of the color palette for the scene…
Resulting TIN Surface
Finally, the resulting profile shows the points reclassified to the correct classification. Repeat for each tile until complete!
We just completed a project for a private landfill here in FL to help settle a contractor dispute about how much dirt was moved/removed from a retention pond. The problem stemmed from the fact that the design engineer estimated the volume as one amount of cubic yards and the earthworks guys sent a bill for twice that amount!
We thought it would be easy by collecting it with airborne LiDAR as part of our flight testing, but then realized that the area in question was a pond that was under water! So, back to the drawing board…
Back in my RCID/Disney days, I worked with some smart people and we learned how to integrate GPS and Bathymetric sensors to map the Hydrilla in their lakes. We also gathered some useful Bathymetric data that could be used to determine target concentrations of herbicides based on a specific dilution factor. The most important part of that equation was knowing the amount of water in the lake and it was a math formula from there on forward. Divide the volume by the target concentration level and you had the amount of herbicide needed to make the brew.
GPS Track of Bathymetric Data
So, we went old school and used our RTK rover to supply a GPS location and the Bathymetric sensor to grab the Z (depth) values for the lake in question. The collection took about an hour and we had a processed and calibrated bathymetric surface before leaving the project site. From there, we integrated the bathy data with the airborne LiDAR to get a continuous representation of the underwater surface.
Solid Rendering of Bathymetric Data with Airborne LiDAR
There was a small discrepancy between the water elevation on the day of airborne collection and the bathy collection. This was handled by surveying the water elevation on the day of the bathy collection and then adjusting all of the depths to this elevation (corrected for the transducer offset which was about 0.1 foot). This gave us the correct elevations relative to the airborne LiDAR data set.
Profile of Bathymetric Data Showing an "Empty" Lake
We determined that the volume of dirt removed was the same as the yield as determined by the design engineer. It turns out that the contractor might have to come to the table to prove that they moved more material then the design engineer predicted and we confirmed with this cool project!
We’re heading to Houston, TX to the SPAR conference next week to demo some new mobile and airborne data and processing tools. This is a great conference for the mobile mapping community and most of our competitors will be there with their latest technology.
We created a marketing video via YouTube to show off the tools we have and how they work – check it out:
We are operational!
Aircraft – Check!
LiDAR – Check!
Aerial Photography Camera – Check!
Hyperspectral Camera – Check!
LiDAR Data Colored by Elevation
We’re operational and have a ton of data in the can and ready for processing. Our data sets include samples from residential communities to transmission powerlines to unmentionable clients who have some interesting needs! One of the biggest hurdles has been developing our own viewing software that we can deliver with these large datasets so that our clients can manage their deliverables. The goal is to build a piece of software that is lightweight and easy to maintain code-wise, while building tools that clients can use to streamline their business processes.
3"-pixel Aerial Photography
Keep watching here for data samples and updates to our software!