We have a project close to home that will involve mobile LiDAR and Airborne LiDAR data capture. We are looking at the absolute accuracies of the data and how they compare along a transportation corridor. The goal will be to collect information related to a DOT’s Right-of-Way (fence to fence) and then collect high-fidelity LiDAR on the road surface that can be used for design/build projects.
The data is in the can and we are in the calibration phase of the project. More to come over the next few weeks showing the sensor data and our project findings…
We’ve wrung out the calibration issues with our mobile LiDAR and we have a solid solution that we can hang our hat on. We have achieved RTK-equivalent accuracies for short runs of less than 5 miles and today, we’re heading out to see how well the accuracies hold up for a 30-mile run.
No worries about having this ready for prime time today – most projects we’re dealing with are only 3-5 miles right now. Our goal is to figure out the best way to keep the GPS solution in check for long runs to avoid post-processing and calibration issues on the back-end of the collect. Since most of the required measurements are “relative”, the LiDAR data is good, but we are striving to crack the “absolute” accuracy nut – and that involves a solid calibration of the equipment. We’ve always known this, but actually “doing” that is a different story!
This is a 5-mile run that we collected here locally. The data has been filtered to a bare pavement surface and we have run cross-sections every 5 feet. Each cross-section can be exported to CAD, GIS, Microstation, etc and used to build pavement resurfacing design drawings.
We have been able to make the processing of this data “semi-automated”. Basically, we have to draw in the breaklines which typically correspond to the pavement stripes. These define the lanes of travel and then we do a slope calculation (relative measurement) from one breakline to another – effectively calculating the cross-slope percentage for each lane. We’re also exporting out a tabular format so clients can use that information to verify the values against a pavement design spec.
Slope 1 refers to the left lane (southbound) and Slope 2 refers to the right lane of travel (northbound) and all slopes are percentages.
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: