Down to 1 cm (0.4 in) drone survey accuracy
Equipped with the 42 MP full-frame Sony RX1R II camera and a multi-frequency PPK GNSS receiver, the WingtraOne surveying drone delivers best-in-class absolute horizontal accuracy, down to 1 cm (0.4 in).
Learn what features allow WingtraOne to achieve this level of accuracy and how these results have been validated.
This level of accuracy is achievable under optimal conditions, on hard surfaces, using a well-established base station or data from CORS network. A minimum of three ground points should be used as checkpoints to verify and prove the accuracy of the project.
Due to the variable quality of photogrammetry, only points validated with checkpoints can be deemed as reaching this level of accuracy and not every point in the point cloud. Find more detailed information in our White Paper and FAQs.
How can WingtraOne deliver this level of accuracy?
Vertical take-off and landing (VTOL)
Most standard fixed-wing drones carry only light 20 MP cameras. They are not powerful enough to take off with a heavier, higher-resolution camera, and belly landings would be fatal for them if they did.
Thanks to its VTOL capability, the WingtraOne can carry heavier payloads such as the Sony RX1R II 42 MP full-frame camera on board and lands without risking damages to it.
High-end PPK receiver
The WingtraOne PPK drone has a built-in multi-frequency (L1-L2 included) PPK GNSS antenna, which ensures best-in-class image geotag correction after the flight.
Along with RTK, PPK is one of the two methods to correct the location of drone mapping data and remove the need for large number of ground control points (GCPs).
For projects requiring accuracy proof, only three ground points should be placed and used as checkpoints to verify the accuracy of the project.
Your own base or correction data
In order to get accurate geotags, you can use either your own base station or correction data from a Continuously Operating Reference Station (CORS) network that is already available. If you use your own base, make sure to set it up in a suitable location with well defined coordinates.
Both the ground sample distance (GSD) and accuracy of a map depend directly on the resolution and the quality of the pictures the drone collects.
In fact, during post processing, the coordinates are defined for each pixel on the map. The selected GSD defines how much ground is captured by a single pixel.
For example, if you fly with a GSD of 3 cm (1.2 in) /px , this is also the best possible absolute accuracy. Thus, in addition to a sharp and undistorted image, the pixel density is a major factor in the level of accuracy the final map can achieve.
In drone photogrammetry, terrain models are generated from a large number of high-resolution photos capturing the surface of the terrain. Therefore, results with such accuracy are possible only on hard surfaces or underneath sparse vegetation where the ground is partially visible from the air.
For specific applications requiring accurate terrain models of soft surfaces or under denser vegetation, drone LIDAR technology might be more appropriate. This is because LIDAR light pulses can filter through small openings between leaves and reach the ground below.
How Wingtra validated the results
|Number of flights||Horizontal RMS error||Vertical RMS error|
To validate the results Wingtra performed two independent tests in the US and Switzerland.
They showcased that, in optimal conditions, the WingtraOne drone consistently achieved an accuracy of down to 1 cm (0.4 in) over 23 flights.
The very small standard deviation value of 0.6 cm (0.2 in) shows that this high level of accuracy is repeatable in every flight.
Total station (tachymeter) and static GNSS at ETH Zurich
In Switzerland, Wingtra used a set of checkpoints from the Institute of Geodesy and Photogrammetry at ETH Zurich (Swiss Federal Institute of Technology). For research purposes, the institute defined the location of these points within 2 mm (0.08 in) horizontal and 4 mm (0.16 in) vertical accuracy. Their readings are based on a high-accuracy network combining total stations (tachymeter) and static long-time GNSS measurements. These measurements are then integrated into a stochastic model that takes into account the accuracy of each device.
The absolute accuracies of the checkpoints are derived from the permanent national CORS network base station located within the area of interest. To learn more about these checkpoints and how their accuracies were defined, read the research paper by Januth and Guillaume (see chapter 3)
A base station and a rover in Phoenix
In the US (Phoenix), Wingtra used two HiPer V GNSS antennas from Topcon. One was set up as a base station and was logging for around three hours. The second was set up as a rover using the correction data from the local base to measure the checkpoints.
Due to the small baseline between the rover and the base station the coordinates were defined at a subcentimeter level relative to the base.
WingtraOne PPK drone with a 42 MP Sony RX1R II camera.
No, we did not use GCPs for processing as photogrammetry software is sensitive to the accuracy and distribution of GCPs, i.e., they can introduce tensions in the block adjustment.
Targets on the ground with known locations are called either ground control points (GCPs), when used for georeferencing, or checkpoints, when used only to validate accuracy after georeferencing. We used checkpoints, which have no influence on the outputs (point clouds, orthomosaics, etc.).
We performed two independent tests in the US and Switzerland. In Switzerland, we used a set of five checkpoints from the Institute of Geodesy and Photogrammetry at ETH Zurich. For research purposes, the institute defined the locations of these points within 2 mm (0.08 in) horizontal and 4 mm (0.16 in) vertical accuracy. Their accuracy is based on a high-accuracy network combining total stations and static long-time GNSS measurements. These measurements are then integrated into a stochastic model that takes into account the accuracy of each device (Januth, T. (2017), chapter three).
In the US (Phoenix), Wingtra used two HiPer V GNSS antennas from Topcon. One was set up as a base station and was logging for around three hours. The second was set up as a rover using the correction data from the local base to measure the nine checkpoints. Due to the small baseline between the rover and the base station the coordinates were defined at a subcentimeter level relative to the base.
We used root mean square error (RMSE) on five (ETH) and nine (Phoenix) checkpoints and measured not just for one but over 14 flights
0.8 cm (0.3 in).
How does centimer-level accuracy translate into real applications?
I was able to provide 0.6 inch (1.5 cm) absolute accuracy over this entire survey area. Aerial-wise, we couldn’t do this without drones.
UAS Operations Manager, SPACECO
Improving log stockpile accuracy by just a couple of inches can mean reducing more than a million board feet in errors resulting in thousands of dollars of estimated profit.
We are used to the helicopter way, but now I can clearly see the advantages of drone photogrammetry. The ease of use of the drone, much faster process and significantly higher data accuracy would help us be more efficient in mine operations
Manager at Kies AG