Measurement Accuracy of Drone
Over the past few years, unmanned aerial vehicles (UAVs), commonly known as drones, have increasingly become a popular tool for aerial data collection in construction, surveying, mining, and insurance. Utilizing photogrammetry, these industries capture aerial imagery and generate valuable insights from large data sets—making it possible to see and measure the changes occurring over time on job sites, mines, and properties.
Photogrammetry is not a new science and has been used for topographic mapping, architecture, and engineering long before the advent of drones. But the rise of computer vision-driven photogrammetry in recent years has paralleled the development of accessible commercial drone hardware and software. The simplicity and automation of today’s solutions allow professionals to integrate these flying robots into existing workflows to map huge swaths of land and generate high-resolution 3D models. This data makes it possible to analyze the world around us more accurately and quickly than traditional measurements, such as ground surveys and manual measurements. In our last white paper, we showed drones can deliver accuracy within 1% of real-world measurements when using Ground Control Points (GCPs).
GCPs are defined points on the surface of the earth that have a known geo-referenced location. By using GCPs in conjunction with aerial photogrammetric data, you’re able to achieve centimeter-level accuracy by “pinning” those points on our aerial map. While accurate, GCPs tend to be a time-consuming process and often require placement throughout the entire duration of a project. When GPS was first used for surveying back in the 1980s, the only way to obtain sub-centimeter positioning with GPS was via post-processing with GCPs, which could take entire days to capture accurately. In the early 1990s, Real-Time Kinematic technology (RTK) was introduced and allowed surveyors to obtain centimeter-level positioning in real-time, with no post-processing required.
In this study, DroneDeploy investigates ways to validate and improve the accuracy of photogrammetric maps with DJI’s Phantom 4 RTK (P4 RTK), a drone that applies RTK technology to aerial imagery. To test the accuracy of the P4 RTK, DroneDeploy created a control point system for a rooftop building survey. Then, 32 flights were logged — each exploring the effect of flight altitude, overlap, and a number of images, on the resulting map accuracy once those images have been processed through DroneDeploy’s Map Engine. These data sets were then used to calculate both the horizontal and vertical accuracy of the measured points, along with the accuracy of linear measurements.
DroneDeploy found that P4 RTK control distances were within 0.27% of GPS Unit measurements, P4 RTK control distances were within 0.1% of P4 Pro with GCP measurements, P4 RTK delivered 2 cm relative vertical accuracy and 1.2 cm relative horizontal accuracy, and that 2D and 3D Flights did not significantly affect measurement accuracy.
Log in with Google