In considering the question of accuracy in the context of UAV Mapping, there are two types of accuracy to consider: Relative (or Local) Accuracy and Absolute (or Global) Accuracy.
Relative (or Local) Accuracy
This is the accuracy of a point on the map relative to other points within the map/model. When asking questions like: "How long is this fence?", "What's the area of this field?", or "What is the volume of this stockpile?", it doesn't matter where the map/model is in the world, as long as the map/model is consistent with itself. This is the important measure for length, area, and volume. For example, if we created a map of Antartica and wanted to measure the shortest distance from the South Pole to the Arctic Ocean we would need high-relative accuracy in our map, meaning the size and shape of Antartica are correct so we find and measure the shortest distance. Say that distance is really 300 miles and we measured it as 300 miles and 20 feet, the relative accuracy of the shortest distance between the South Pole and the ocean would be within 20 feet.
Absolute (or Global) Accuracy
Absolute accuracy is the degree in which the calculated position of a point on a map corresponds to its actual position in a fixed coordinate system in the real world. If a map has a high level of global accuracy, the latitude and longitude of a point on that map will correspond fairly accurately with actual GPS coordinates. This is important when you need a high degree of confidence that the lat/long and elevation measurements of each point on the map are correct when comparing with the real world, i.e., when comparing to geo-referenced design documents for a construction project or conducting property boundary surveys. Using the map of Antartica as an example, the absolute accuracy of the location of the South Pole is the difference between where it is on our map and where the real South Pole is located. If the map shows the South Pole 2 feet to the left of where it should be, then the absolute accuracy of that point is within 2 feet.
What Accuracy Can I Typically Expect?
Note: Due to the myriad of factors which influence the accuracy of UAV derived map data, it is not possible to give definite definitive measure of either local or global accuracy. The examples described herein are intended to provide a reasonable estimate but these should not be regarded as absolute values. For mission critical applications which require known error reporting or are particularly sensitive to Absolute Global Accuracy, UAV based estimates should be validated with on site measurements or referenced with known entities on site.
There are a number of factors which will affect the final accuracy of a processed map including:
Camera: Bigger and better sensors have less noise, less blur, and less of a rolling shutter effect, which will produce better data.
Lens: Less lens distortion (barreling or fisheye) will produce better data.
Drone: Drones with gimbals that stabilize the camera angle will produce better data.
Altitude: The higher one flies, the less accurate things like elevation will be as it's harder to tell the relative difference between two distances the further one is away from it.
Image resolution: Higher-resolution imagery will produce better data because there's more information to match against.
Number of photos: The more images, the more GPS locations there are to work with. This in turn produces less error.
Higher Overlap in imagery: The higher the overlap in images, the more key-points can be detected in the processing software we use and in turn, the more GPS data we'll have for each pixel, increasing accuracy.
Atmospheric Conditions: GPS is affected by: Atmospheric Conditions (temperature, air density, pollution, clouds), Ionospheric conditions, Solar Flares
Buildings: Tall structures block GPS signals, as well as reflect them (commonly called the "Urban Canyon") causing multi-path interference which causes inaccurate data.
Location on Earth: There are several GPS constellations (see below), and where you are on Earth limits the number of satellites you can access.
- GPS in the US
- GLONASS in Russia
- GALILEO in Europe
- BeiDou-2tf in China
- NAVIC/IRNSS in India
- Where GPS and GLONASS are the only Global systems, the others only have local visibilityGPS Receiver: Different GPS receivers listen to different constellations (listed above). The ability to accept more signals give more statistics to use for positioning which improves accuracy.
Multivista uses high quality profesional-grade UAVs and our operators are trained to follow procedures which optimize as many of the above factors as possible.
Relative Accuracy
The horizontal accuracy within a map largely depends on the Ground Sampling Distance (GSD, i.e., number of pixels per centimeter) of the data. The local error is typically seen to be ranging from 1 to 3 times the average GSD of the data. Multivista standard operating procedures target a GSD of 0.5 to 2 inches / pixel depending on allowable flight altitudes. This can be expected to result in a typical relative accuracy of somewhere between 0.5 - 6 inches.
Absolute Accuracy
With standard Multivista equipment and operational procedures, one can typically expect to have approximately 1 meter (3 ft) horizontal accuracy. So, if one draws a circle around yourself with a 1m radius, and gives someone your GPS location, they're expected to be somewhere within this circle. The Absolute Vertical Accuracy is typically around 3 times poorer than the horizontal so one would expect approximately 3 meters.
Source: https://support.dronedeploy.com/docs/accuracy