Analysis of processing outputs
Panu Srestasathiern, PhD. Researcher Geo-Informatics and Space Technology Development Agency (Public Organization)
Analyzing the processing report • Orthophoto and digital elevation model sketch; • Camera parameters and survey scheme • Tie points data export (matching points and panoramas) • Image overlap statistics • Camera positioning error estimates • Ground control point error estimates
Ground Control Points • Error report
Ground Control Points • Error report
Camera calibration report • What are these parameters?
Analyzing the processing report • While carrying out photo alignment, a photogrammetric software estimates both interior and exterior camera orientation parameters, including nonlinear radial distortions.
Image residuals • The geometric error corresponding to the average image distance, measured in pixels, between:
Image residuals • This reprojection error is equivalent to the root mean square (RMS) image residuals used in photogrammetric literature
DSMs comparison -GCPs • When no airborne GPS is available.
'Bowl effect' effect' • effect can be introduced during photo alignment, in case camera calibration estimates are inaccurate
'Bowl effect'effect'- solutions to the problem • Use GCP
Bowl effect is also called Toblerone-effect.
'Bowl effect'effect'- solutions to the problem
Digital Orthophotos – tricky surfaces
Digital Orthophotos – tricky surfaces
Defining Accuracy for UAV Maps • When it comes to UAV mapping, there are two ways to think about accuracy: – relative accuracy – absolute accuracy.
Relative (or local) accuracy • Relative accuracy is the degree to which a given point on a map is accurate relative to other points within that same map. • In other words, if a distance between two points measures 10 inches in the real world, it also measures 10 inches on your map.
Relative (or local) accuracy • For example, the shortest distance from the South Pole to the Arctic Ocean is really 300 miles and we measured it as 300 miles and 20 feet on our map. The relative accuracy of the shortest distance between the South Pole and the ocean would be within 20 feet.
When to use relative accuracy • Relative accuracy is usually sufficient for projects like taking small-scale measurements, visually inspecting progress on construction sites and monitoring fields for crop health. • Essentially, any time you need to gather information from within a map itself, but do not necessarily need to place that map accurately in space.
When to use relative accuracy Projects for which relative accuracy is usually sufficient: • Small-scale measurements — e.g., area of a field, length of a fence, width of a stockpile • Management and oversight — e.g., keeping tabs on general progress of a construction site • Crop scouting — e.g., assessing damage after a storm, monitoring crop health • Marketing — e.g., creating a time-lapse or 3D model project to share with prospective clients
Absolute (or global) accuracy • Absolute accuracy is the degree to which a point on a map corresponds to 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. • For example, in our giant map of Antartica, 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. 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.
When to use absolute accuracy • Absolute accuracy becomes important when you need a high degree of confidence that the latitudinal, longitudinal and elevation measurements are correct, such as when combining your map with other geo-referenced data sets.
How to Check the Absolute Accuracy of Your Map • The accuracy of a map is expressed as the average error between points coordinates which are estimated from aerial triangulation, and ones measured with GPS. • The larger the error between the two, the lower the data accuracy.
What Accuracy Can You Expect? In general, given average conditions and a typical drone, you can expect approximately the following ranges of accuracy: • Relative accuracy: Is typically a multiple of your data’s average Ground Sampling Distance (GSD). The horizontal relative accuracy is 2x GSD (for example, if your GSD is 2 cm/pixel, the horizontal accuracy will be approximately 4 cm) and the vertical relative accuracy is typically 3x GSD.
What Accuracy Can You Expect? In general, given average conditions and a typical drone, you can expect approximately the following ranges of accuracy: • Absolute accuracy (Without GCP): Absolute horizontal accuracy: approximately 1 meter – If you draw a circle around you with a 1 meter radius, and give someone your GPS location, you can expect them to turn up somewhere within this circle.
Absolute vertical accuracy: approximately 3 meters – As a rule of thumb, the absolute vertical accuracy of a map will be around 3 times worse than its absolute horizontal accuracy
What Accuracy Can You Expect? In general, given average conditions and a typical drone, you can expect approximately the following ranges of accuracy: • Absolute accuracy (With GCP): One can radically improve your Absolute (or Global) GPS accuracy by using Ground Control Points (GCPs) or Differential GPS systems (RTK, PPK, etc.). Absolute horizontal accuracy: approximately 2-5 cm Absolute vertical accuracy: approximately 4-8 cm
What affects my Accuracy? • Camera: Better and bigger 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 keeping the camera pointing correctly will produce better data • Altitude: The higher you fly, the less accurate things like elevation will be as it's harder to tell the relative difference between two distances the further you are away from it.
What affects my Accuracy? • 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 we have to work with. This produces less error because of the Law of large numbers • Higher Overlap in imagery: The higher the overlap in images, the more key-points we can detect, and the more GPS data we'll have for each pixel, increasing accuracy
What affects my 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 multipath interference which causes inaccurate data
What affects my Accuracy? • Location on Earth: There are several GPS constellations (see below), and where you are on Earth limits the number of satellites you can – 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 visibility
What affects my Accuracy? • GPS Receiver: Different GPS receivers are able to listen to different constellations (listed above). Being able to accept more signals give more sats to use for positioning which improves accuracy. • Differential GPS: RTK, PPK etc. has access to corrections of the GPS data which radically improves accuracy (meters -> cm).
How can I increase accuracy? The biggest improvements can be made by: • Using a Differential GPS Differential GPS systems like RTK and PPK will radically increase your accuracy. RTK typically produces an absolute horizontal accuracy of within 1 to 3cm. • Using Ground Control Points Ground control points add another layer of location data to the map, rather than relying solely on the GPS of the drone.