Full text: Papers accepted on the basis of peer-reviewed abstracts (Part B)

In: Wagner W., Székely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
360 
RADIOMETRIC CALIBRATION OF FULL-WAVEFORM AIRBORNE LASER SCANNING 
DATA BASED ON NATURAL SURFACES 
Hubert Lehner a and Christian Briese a b 
a Christian Doppler Laboratory, Institute of Photogrammetry and Remote Sensing, 
Vienna University of Technology, Gusshausstrasse 27-19, 1040 Vienna, Austria, 
(hi, cb)@ipf.tuwien.ac.at 
b Ludwig Boltzmann Institute for Archaeological Prospection and Virtual Archaeology, 
Hohe Warte 38, 1190 Vienna, Austria 
Commission III/3 
KEY WORDS: Radiometry, Radiometric Calibration, LIDAR, Laser scanning 
ABSTRACT: 
Airborne laser scanning (ALS) has become a commercially available and therefore widely used technique for obtaining the geometric 
structure of the earth’s surface. For many ALS applications it is beneficial or even essential to classify the 3D point cloud into 
different categories (e.g. ground, vegetation, building). So far, most classification techniques use the geometry of the 3D point cloud 
or parameters which can be gained from analyzing the geometry or the number of echoes per emitted laser shot. Decomposing the 
echo waveform of full-waveform laser scanners provides in addition to the 3D position of each echo its amplitude and width. These 
physical observables are influenced by many different factors (e.g. range, angle of incidence, surface characteristics, atmosphere, etc.). 
Therefore, these attributes can hardly be used without radiometric calibration. In this paper the theory of the radar equation will be used 
to transform amplitude and echo width into radiometric calibration values, such as backscatter cross section, backscattering coefficients 
or incidence angle corrected versions of those. For this aim, external reference targets with known backscatter characteristics are 
necessary for the absolute radiometric calibration. In contrast to other approaches, this paper presents the usage of natural surfaces for 
this calibration task. These surfaces are observed in order to determine their backscatter characteristics independently from the ALS 
flight mission by a RIEGL reflectometer. Based on these observations the data of the ALS flight can be calibrated. Calibration results 
of data acquired by a RIEGL LMS-Q560 sensor are presented and discussed. Next to a strip-wise analysis, the radiometric calibration 
results of different strips in the overlapping region are studied. In this way, the accuracy of the calibration is analyzed (1) based on 
a very large area with approximately homogeneous backscatter characteristics, namely a parade yard, and (2) relatively by analyzing 
these overlapping regions. 
1 INTRODUCTION 
Airborne laser scanning (ALS, also referred to as airborne LI 
DAR (light detection and ranging)) is an active sampling method 
that is widely used for obtaining the geometric structure of the 
earth’s surface. The resulting point cloud is a good basis for 
the modelling of the landscape for a variety of applications, e.g. 
hydrology (Mandlburger et al., 2009), city modelling (Rotten- 
steiner et al., 2007), forest mapping (Naesset, 1997, Hollaus et 
al., 2007), archaeology (Doneus et al., 2008). For these applica 
tions it is typically necessary to classify the ALS data into dif 
ferent classes (e.g. ground, vegetation, buildings). Most of the 
developed classification methods just rely on the geometric infor 
mation provided by the acquired point cloud. However, with the 
introduction of small-footprint full-waveform (FWF) ALS sen 
sors into the commercial market further additional attributes, i.e. 
the echo width and amplitude, for each echo can be determined. 
These attributes can be seen as physical observables that allow 
studying the radiometry of ALS data. However, in order to uti 
lize this information a radiometric calibration of the ALS data is 
essential (Wagner et al., 2008b). 
For the radiometric calibration of ALS data different methods 
were already published. Next to their mathematical or physi 
cal framework the approaches differ in the use of reference data. 
Some publications do not use reference surfaces at all and only 
try to compensate for specific influencing factors (Luzum et al., 
2004, Donoghue et al., 2007, Hôfle et al., 2007). Another group 
of authors rely on artificial reference targets that were placed 
within the area of interest during the data acquisition campaign 
(Ahokas et al., 2006, Kaasalainen et ah, 2007), while the third 
group of researchers tries to solve the radiometric calibration task 
with the usage of natural reference targets (Coren and Sterzai, 
2006, Wagner et ah, 2006, Briese et ah, 2008). 
Within this paper the practical application and validation of the 
radiometric calibration of small-footprint FWF-ALS data based 
on natural surface elements is presented and studied. The calibra 
tion procedure relies on the radar equation (Wagner et ah, 2006) 
and on natural reference surfaces. These surfaces are observed 
in-situ by a RIEGL reflectometer (Briese et ah, 2008). Based on 
these observations, the data of the ALS flight can be calibrated. 
In order to demonstrate the practical capability and to study the 
quality of the radiometric calibration this process is applied to 
an FWF-ALS data set acquired by a RIEGL LMS-Q560 sensor 
over the city of Vienna, Austria. Next to the practical application 
of the method the resulting calibrated data set is analysed strip- 
wise by a visual comparison of the radiometric information in the 
overlapping area of two strips. Furthermore, a quantitative com 
parison of the calibrated data sets is performed by an analysis of a 
difference model in the overlapping zone. Finally, after the dis 
cussion of the results, a short summary and an outlook into future 
research work conclude the paper. 
2 RADIOMETRIC CALIBRATION 
2.1 Theoretical Background 
The basic relation between the transmitted power Pt and the re 
ceived power P r of an ALS system can be described by the LIDAR
	        
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