In: Wagner W., Szekely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
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as the most valuable input for sophisticated scientific analysis 
including deriving target physical properties (Chauve et al., 
2009a). It has been demonstrated that full waveform data 
provide a significantly more complete and accurate assessment 
of the surface, the canopy and potential obstruction detection 
than the discrete return system (Magruder et al., 2010). 
Moreover, full waveform lidar data capture gives the user much 
more flexibility and control in data processing and 
interpretation steps (Chauve et al., 2009b). However, dealing 
with full waveform datasets takes lidar data management to a 
drastically higher level of complexity compared to conventional 
3D point cloud data. First, the volume of full waveform data is 
overwhelming: about 140 GB for 1.6 hours of data acquisition 
time at a 50-kHz pulse repetition frequency (Chauve et al., 
2009b). This can be compared to 12 GB of discrete-return data 
with four full records (four ranges, four intensities) for the same 
acquisition time and pulse frequency (Optech). Moreover, there 
are neither commercial nor open-source toolkits to handle full- 
waveform lidar data, but only custom-made solutions typically 
designed for specific sensors (Bretar et al., 2008). Therefore, 
managing full-waveform lidar data is a very challenging and 
expensive task. This limits the commercial use of full 
waveform lidar data, confining it mainly to research 
institutions. 
This paper presents a revolutionary change in the discrete 
return airborne lidar technology. It will show that the new, most 
advanced airborne lidar system—ALTM Orion—manufactured 
by Optech Incorporated, is capable of mapping targets with 
complex vertical structure with much higher resolution than has 
ever been available before in any discrete return airborne lidar. 
A simplified waveform analysis of high-resolution discrete 
return data collected over low and medium canopy vegetation 
will be presented and discussed in the context of methodology 
typically used for full waveform data analysis. It will show that 
the new-generation discrete return airborne lidar technology 
can provide quality data and some characteristics approaching 
that of full waveform data. 
2. EVOLUTION OF DISCRETE RETURN AIRBORNE 
LIDAR TECHNOLOGY 
Initial commercial airborne lidar systems, such as Optech’s 
ALTM 1020, 1210 and 1225 models manufactured between 
1993 and 1998, had the ability to capture only two returns (first 
and last) for each emitted laser pulse. This feature, though 
seemingly modest compared to the capabilities of contemporary 
advanced airborne lidar systems, already provided enriched 
information for sophisticated analysis of both returns for 
potential applications such as feature extraction in forest 
(Hopkinson et al., 2004; Roberts et al., 2005) or urban areas 
(Alharthy and Bethel, 2002). With further evolution of lidar 
technology, more advanced ALTM models capable of capturing 
four range and four intensity returns became commercially 
available, and for the last decade the maximum number of 
multiple returns per emitted laser pulse has been stabilized at 
this limit. 
However, as mentioned, not only the number of multiple 
returns is important for the proper mapping of targets with a 
complex vertical structure, but also the minimal discrimination 
distance between two consecutive returns. The vertical 
discrimination distance, that is, minimum distance (time) 
separation between consecutive pulse returns, is solely 
determined by the lidar system hardware design, and along with 
range precision it would determine the type, quality and 
accuracy of the consequent data analysis based on discrete 
return data. In most commercial discrete return lidar systems 
the minimal pulse discrimination distance is close to 2-3.5 m 
(Optech ALTM 3100 and Gemini, Leica's ALS series). This 
means that targets separated by any distance less than this 
minimum cannot be resolved by consecutive multiple returns. 
Until recently the numbers characterizing minimal target 
separation distances had not been typically specified in the brief 
data sheets of most commercial lidar systems, but could be 
found in more detailed specification documents, or provided to 
users upon request. This situation created some 
misunderstanding in the lidar community as users expect to 
detect four discrete returns from objects a few meters high 
objects without considering the minimum vertical 
discrimination distance. The lack of knowledge of this 
parameter may also lead to misinterpretation of multiple return 
data and even gross systematic errors due to wrong 
interpolation. Since the minimum target separation distance 
seems to be one of the best performance parameters to 
characterize the ability of an airborne lidar system to map 
complex vertical targets, it is very important for users to have 
this knowledge. 
Figures 1-2 present typical examples of multiple return data for 
the ALTM 3100 and Gemini systems. In both cases the laser 
beam penetrated through 16-20 m of vegetation, and the last 
return with strong intensity clearly indicates the signal reflected 
from the ground. 
Figure 1. ALTM 3100: An example of a four-return record 
for one emitted laser pulse with a minimum pulse separation 
distance of 2.14 m. 
Figure 2. ALTM Gemini: An example of a four-return record 
for one emitted laser pulse with a minimum pulse separation 
distance of 1.45 m. 
Although these two examples represent leading-edge discrete 
return airborne lidar technology, it is clear that full waveform