QUALITY CONTROL METHOD FOR FILTERING IN AERIAL LIDAR SURVEY 
Y. Yokoo 3 ’ *, T. Ooishi 3 , 
3 Kokusai Kogyo CO., LTD. ,Base Information Group, 
2-24-1 Harumicho Fuchu-shi, Tokyo, 183-0057, JAPAN - (yasuhiro_yokoo, tetsu_ooishi)@kkc.co.jp 
Commission WG 1/2 
KEY WORDS: LIDAR, Filtering, QC/QA map, Shaded Relief, Ground Point Data, Original Point Data , 
ABSTRACT: 
The purpose of filtering LIDAR data is to extract the laser points which are truly reflected from the bare ground. However, the 
results obtained may vary since several engineers are involved in the manual filtering process. For this reason, the QC/QA maps are 
created in Japan after the filtering process in order to control the filtering quality. This paper describes a quality control method 
using an original and a unique QC/QA maps. We use two types of QC/QA maps to check the filtering results: one is a color-shaded 
relief map and the other is our monochrome-shaded point maps. The reason we use two types of QC/QA maps is that they have 
different purposes. The purpose of color-shaded relief map is used to inspect the detailed noise data. In contrast, the purpose of a 
monochrome-shaded point map is to examine the over-elimination of point clouds during the filtering process. Using these two types 
of maps together, we are able to extract from the point clouds obtained by airborne LIDAR that are truly reflected from the bare 
ground. Finally, we have carried out image analysis of monochrome-shaded point maps to automatically extract the erroneously- 
eliminated points from the point clouds. Some results of automatic extraction are also reported. This quality control method will 
certainly improve the quality of the filtering process for the airborne LIDAR points. The method described can be applied not only 
to airborne LIDAR but also to terrestrial laser surveys. However, more study on the automatic examination is needed in the future, 
and some considerations regarding to the automatic examination are also described in this paper. 
1. INTRODUCTION 
An airborne LIDAR system makes it possible for the speedy 
acquisition of high-density/high-accuracy three-dimensional 
(3D) topographic data at low cost. These 3D topographic data 
have become available for various purposes including flood 
control and environmental protection measurements. 
Among their applications is the hydraulic analysis of rivers to 
evaluate the safety level of flood control measurements. As the 
results of this analysis affect human lives and properties, it is 
extremely important that the presentation of topography 
provided by the 3D topographic data be accurate. 
So far, attention has been paid to the elimination of 3D data 
from feature data such as trees and structures in the process of 
Airborne LIDAR, and many cases of elimination using 
automatic processing algorithms and commercially available 
software have been reported. Although these tools are excellent, 
automatic filtering tends to leave intact feature data that should 
have been eliminated and instead eliminate measured point 
groups from increasing slope points that should be adopted as 
ground point data, such as the tops of slopes of banks. Figure 1 
shows the cross sections of a river which is created from both 
automatically filtered and manually filtered data. The figure 
shows that the automatic filtering has eliminated bank data on 
the right side of the figure. This elimination expands the cross 
section of the river channel and thus affects the hydraulic 
calculation. Therefore, point groups erroneously removed from 
the laser data during the automatic filtering have to be retrieved 
manually. This process is referred to as manual filtering. As 
manual filtering involves judgments made by operators in the 
interpretation of reference materials, different filtering results 
are obtained from different operators. To solve this problem, 
QC/QA maps are prepared to verify the quality of the filtering. 
We have been implementing a unique quality control method 
that is devised as in-house processing. We use two types of 
QC/QA maps in the quality control processing. One is a 
monochrome shaded point map, the other one is a color-shaded 
relief map. The monochrome shaded point map is a new 
QC/QA map devised by us. 
This paper describes a quality control method using 
monochrome shaded point maps and color-shaded relief maps. 
At the end, we report the results of automatic point-extraction 
using a monochrome shaded point map for a river bank and its 
slopes. 
2. DESCRIPTION OF SHADED POINT MAP 
2.1 Description of Monochrome-Shaded Point Map