I’ve been hearing the term PhoDAR (photogrammetric detection and ranging) a lot lately. There are numerous automated “photogrammetry” software packages being offered today that create point clouds from photos. The software looks phenomenal and many boast of incredible accuracy. Wikipedia currently lists more than 60 such solutions, with big name vendors such as AutoDesk, Bentley, Microsoft, and Trimble on the list.
These software solutions utilize camera based techniques that rely strongly on a workflow called Structure from Motion (SfM). During the SfM process, 2-Dimensional photographs of a scene are obtained from many different perspectives, the software then analyze the photos looking for similar features and patterns. Using this redundancy the software estimates a camera calibration as well as transformations between the different camera views. Typically this is done in multiple steps with an initial “sparse processing” to determine camera and view parameters, and then a “dense reconstruction” is performed that processes the images in overlapping chunks. This technique is computationally intense, but uses statistics to estimate reality and come up with a point cloud. If the same pattern matches in multiple photos a level of confidence can be estimated that point actually exists… even if it doesn’t.
I’ve been exploring this technology for nearly a decade and it has been interesting to see the market develop. In one recent Whitepaper eBee (using Pix4D I’m guessing) claims they can achieve an accuracy of 3 cm (Horizontally) to 5cm (Vertically). My guess is the key word there is “can.” Just because it can be done, doesn’t mean it is done. (How’s that for a sentence?)
If you’ve ever tried out this type of software you’ll notice glaring issues if you look at the data closely. An example of this is provided below. The far left is a photograph of the actual pole, the middle data was collected with our Faro terrestrial scanner, and the far right was computed using a very popular (and expensive) software SfM/PhoDAR/Photogrammetry package. Reality and LiDAR are very clearly in agreement, but the limitations of structure-from-motion based solutions are apparent. This point cloud was computed using 30+ images at an altitude of 150 feet (more to come on this example later).
It is interesting technology and those high-altitude demo videos I keep seeing are impressive, but I don’t think it’s quite a substitute for professional grade mapping. As this software becomes more accessible, there’s a potential danger to the public when used by drone owners who may not know the limitations. Be careful out there and stay informed, check back here often for more on this topic as we continue to explore new geospatial technologies.
Please comment below and share your opinion on PhoDAR and other automated photogrammetry solutions. Does automated photogrammetry pose a risk to the public?