Vegetation management around runways and taxiways is a common and necessary task at regional airports that requires high accuracy tree height measurements and details to preserve take-off and landings. The Federal Aviation Administration (FAA) outlines how airport owners and operators should collect, submit, and manage vegetation data that might affect safe and efficient airport operation. These survey details range from tree classifications to above ground height of trees, measured above the base and tree locations, based on the runway and the airport elevation.
While a conventional ground-based survey approach to measure tree locations is ordinarily satisfactory, publicly owned and operated Charleston Executive Airport in John’s Island, South Carolina, faced a more challenging situation with some complicating variables.
The density of the wooded areas off the end of the airport’s two runways stretched beyond the airport limits. Therefore, maintenance crews had no effective way to access the area to accurately measure and identify which trees infiltrated the aircraft glide slope onto the runway.
With an eye on detailed remote sensing data, safety and speed, the airport manager looked to SAM and its technology-enabled toolbox for help.
Coordinated Visuals
For the tree-height data gathering, the airport needed to identify, locate, and measure the height of trees located at the end of two runways, RW4 and RW9.
SAM proposed a UAS-based approach, to identify the height of the trees that penetrated the glide slope at end of each runway as well as the stretch beyond the airport’s limits. We utilized the ORC2 single-rotor Unmanned Aerial Vehicle (UAV) electric helicopter equipped with a REIGL mini VUX-1 UAV airborne laser scanner with waveform-LiDAR technology. LiDAR can capture data through dense vegetation and when combined with the UAV, can capture data in areas that are less ideal for larger, heavier aircrafts.
Prior to the operation, SAM worked with the airport’s team to develop and publish an Airport Notice to Airman (NOTAM). The NOTAM contained information for essential flight personnel about the Unmanned Aerial Systems (UAS) flight schedule and area of operation to ensure manned aircraft traffic could land and take off safely with limited impact. For added safety purposes, SAM utilized a third observer to conduct real-time flight coordination with incoming and outgoing manned traffic.
In a total of four hours over two days, SAM crews completed the low altitude LiDAR-based data collection at the end of the runways. The resulting georeferenced 3D point cloud had a high density of 60-points-per-square-meter and the imagery had a 2-inch resolution.
Beyond Identification
Once processed, the data file included a total of 3,976 trees that were automatically identified from the dense point cloud compiled by SAM. Further, our team developed a custom algorithm to extract tree trunk height above the surface to support a trim list for the airport vegetation management crew.
“This was a very special project for our UAS crew in the Carolinas,” said Luiz Cortes, SAM Operations Manager in the Aerial Mapping service sector. “Our team developed a low altitude LiDAR collection plan that allowed us to safely fly our UAS at the end of the runways, without any commercial flight interruption. There was no delay in the collection and no incidents on this challenging aerial mission—and we were able to provide the client with an accurate and effective work product to manage their vegetation in this unique environment.”
Our Aerial Mapping service sector has completed over 10,000 UAS flights since 2018 by keeping client asset safety and security at the core of our program. Read more about our program’s success here.