The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Voi. XXXVII. Part BI. Beijing 2008 
surface, profile vs profile, surface (shape) vs shape, to evaluate 
the quality of Airborne LiDAR. 
2. FACTORS AFFECTING ACCURACY OF LIDAR 
DATA 
- Time latency (In such a system as a whole, the time 
synchronization of the important role, e.g., GPS and 
laser finder system synchronization problems. GPS of 
measuring the rate of general in dozens of Hz, but the 
laser canner of measuring the rate of in 10 to 100 kHz) 
The quality of laser scanning has been studied during the last 
few years (e.g. Crombaghs et al., 2002, Ahokas et al., 2003). It 
has been shown that the terrain height can be typically collected 
within 15 cm. But, in fact, there are large numbers of factors 
affecting the quality and accuracy obtained, e.g. the surface 
material, flight altitude of sensor and platform, GPS/INS and 
observation angle, and so on. 
2.1 The criteria of positional accuracy 
The NSSDA (National Standard for Spatial Data Accuracy) 
uses root-mean-square error (RMSE) to estimate positional 
accuracy. RMSE is the square root of the average of the set of 
squared differences between dataset coordinate values and 
coordinate values from an independent source of higher 
accuracy for identical points. 
RMSE X = sqrt^ix^-x check i) 2 In] (2) 
RMSE y = sqrt [£ { ydata i - y check . f I n\ (3) 
RMSE z =sqrt\Y j {z datai -z checki ) 2 In] (4) 
Where: 
x data,i ’ ydataj ’ Z da,a,i are the coordinates of the i th check 
point in the dataset 
x check,i ’ ycheck,i ’ z check,, are the coordinates of the i th 
check point in the independent source of higher accuracy 
VI is the number of check points tested 
i is an integer ranging from 1 to n 
2.2 The errors in LiDAR 
Concerning data accuracy, the major error sources in LiDAR 
are the following: 
- Positioning of the platform (Satellite has a major role 
in GPS positioning reliability. It is quantified by 
Positional Dilution Of Precision (PDOP). Poor 
satellite, in other words, a high PDOP, generates 
inaccurate GPS coordinates.) 
- Orientation determination from IMU (The error from 
the IMU is as systematic differences on strips depend 
strongly on the error from the IMU. The IMU is one 
of the main causes of horizontal error in scanned data 
points, and errors very often increase or decrease with 
consistency in a flight’s direction.) 
- Offsets between the laser sensor, INS/POS equipment 
and an aircraft platform 
- Errors in the electro-optical parts of the laser sensor 
- Wrong laser and INS/POS data processing 
- Integration and interpolation of the INS and GPS data 
- Erroneous data from the reference ground GPS base 
stations, or, there are no enough base stations 
- Data coordinate transformation 
3. WORKING FLOW AND METHODOLOGY 
As discussed by the LiDAR equation (Equation 1), there is no 
redundancy in LiDAR measurements. This is because, due to 
the random nature of LiDAR points, one cannot measure the 
exact same point in different strips. Therefore, unlike with 
photogrammetric data, one cannot use explicit measures to 
assess the quality of LiDAR derived positional information. 
Therefore, alternative quality assessment methods are necessary 
for this type of data. 
According to author's data processing experience and other 
literature, a working flow of data processing based on 
progressive quality control, is put forward as Figure 2. 
Relative 
Absolute Quality 
Figure 2. Working flow of LiDAR data processing 
Against every step in above figure, its methodology could be 
discussed following.