- Dr. Habib, from the Univ. of Calgary is one of the experts in this area.
- LiDAR is much more of a black box than photogrammetry in terms of system calibration.
- QA occurs before the data collection and QC after.
Before attempting to make a few points on this important topic I want to provide a disclaimer. I am still in the process of learning about these issues particularly as they apply to LiDAR. I can provide links to people who are experts in this area, such as Ayman Habib and one of his students, Kutalmis Saylam who I have blogged about previously, and who are both associated with the Univ. of Calgary.
In fact Dr. Habib wrote the book, well actually the chapter in Shan and Toth’s book entitled, Topographic Laser Ranging and Scanning on QA/QC. I have mentioned this text before. It is a must reference source if you want to understand the science and art behind laser scanning, particularly as it applies to the airborne and also mobile platforms.
The first key understanding is that LiDAR calibration, unlike photogrammetry, is not a transparent process. The LiDAR sensor is not independently calibrated as with a camera. It is in effect a black box in terms of internal calibration. You are reliant on the equipment manufacturer.
Secondly, derived data is not based on redundant measurements which can be manipulated in a Least Squares adjustment process. You therefore cannot evaluate your results using a pure mathematical approach. In effect you must rely on methods that determine if the data is consistent when derived from overlapping strips. The data will only represent the same surface in both flight lines if there are no biases in the system.
A third point is in understanding the difference between QA and QC. QA is a pre-flight management process that looks at calibration, planning, and implementation of the proposed data collection activities. QC takes place after the data is collected to determine if the desired quality has been achieved.
There are of course random and systematic errors. Some of the latter involve boresighting offset and angular biases, and laser range and angular errors. Random errors or what is sometimes referred to as noise, make up the other part of the error budget. These are more difficult to quantify and eliminate. They include GPS, sensor angular and range noise. Random noise is commonly thought of as not affecting accuracy, but that is not the case for LiDAR.
Finally, QC procedures can be divided into 2 categories – external or absolute, and internal or relative. External involves the use of pre-targeting and on the ground survey, while internal as mentioned above involves comparing data from adjacent flight lines for the same ground features.
As noted in the past, hiring an independant firm to manage the QA/QC is often a wise investment. Off to my first day of rowing for the new season.
