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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B2. Istanbul 2004 
  
use of them. Educated users, especially research organisations, 
will always be keen to look at new products, but users more 
familiar with photographic products will take more time. Some 
of the major users of both airborne LiDAR and IfSAR have 
been new users, for example power generation companies for 
powerline survey, and insurance companies for assessing flood 
risk. But there can be problems with such users not 
understanding the characteristics of the data, nor the accuracy 
which can be expected. 
LiDAR can produce a high density of points, and although this 
is an advantage in some situations, it can also cause problems, 
for example in the volume of data to handle. High density 
might be necessary to identify detail on the ground, small 
gullies or crash barriers on highways for example, but not on 
the main carriage way. Thus there is a problem on how to this 
the data to retain only what is needed. Intensity images may 
appear to be useful in order to make it unnecessary to fly a 
camera as well, but their quality is not as good, and there is no 
standard for measuring intensity. On the other hand flying a 
camera with the LiDAR can be a disadvantage as it means that 
the lighting conditions must be good enough for the camera, 
whilst the LIDAR could operate in poorer lighting conditions. 
IfSAR is a complex system and users do not need know the 
intricacies of the processing, but they do need to understand 
that SAR samples a footprint which is quite large and that 
different types of land cover give different responses. They also 
need to understand the meaning of orthocorrection, (terrain 
orthoimages and true orthoimages), the need for compatibility 
of projection and datum, and the significance of error statistics. 
In other words the users need to be educated to some degree and 
the data provider needs to ensure that they are. 
In the United Kingdom, the Highways Agency has produced a 
specification for LIDAR surveys which has been produced in 
close consultation between the data providers and the client. 
This ensures that the client gets what is needed, for example in 
terms of data formats, and visualisation of products to help new 
users, and the provider understands what is required. 
13. APPLICATIONS 
13.1 Introduction 
There are now a great many applications for DEMs from 
LiDAR and IfSAR data and it is beyond the scope of this paper 
to deal with all of them. We will therefore briefly review some 
of the innovative applications and concentrate on those which 
involve the use of data from more than one source. 
13.2 Regional and global mapping 
IfSAR has proven itself for low cost DEM generation over large 
areas. The prime example is SRTM, but large areas have also 
been mapped with ERS data, for example the Radarmap of 
Germany (Kosmann et al, 1994). Airborne systems have been 
used for generation of DEMs and orthoimages over large areas 
such as the Nextmap Britain project (Mercer, 2003a, Dowman 
and Fischer, 2003). The Nextmap data was originally 
commissioned for an insurance company for flood risk analysis, 
but is now being used more widely than that, and is 
complementary to LiDAR, which is useful in denser urban 
areas. Intermap have carried out IfSAR surveys in many parts 
of the world including Malaysia and Indonesia, and are starting 
on a coverage of the whole of the USA. 
907 
13.3 Environmental applications 
À major application for environmental use is forestry. The 
ScandLaser Scientific Workshop of Airborne Laser Scanning of 
Forest, held from September 3-4, 2003 in Umea, Sweden, gives 
a very detailed view of the current status of LiDAR for forestry, 
e.g Wulder (2003), Naesset (2003), Hyyppa et al (2003). 
Hamdan (personal communication) has noted that Dubayah and 
Drake (2000) listed the key forest characteristics that can be 
measured directly or indirectly by LiDAR. Among the 
parameters that can be retrieved directly are canopy and tree 
height, timber volume, forest mixtures according to tree species, 
natural age classes, forest canopy closure, decision of forest / 
non-forest and sub canopy topography. Beside this, above 
ground biomass and volume, basal area, mean stem diameter, 
vertical foliar profiles, canopy volume and large tree density can 
either be modelled or inferred from LiDAR measurements. 
Other important parameters for forest such as canopy cover, leaf 
area index (LAI) and life form diversity need aifferent approach 
where data fusion from lidar and other sensor is essential. In this 
case, the vertical component provided by LiDAR should be 
fused with information from passive optical, hyperspectral, 
thermal and radar remote sensing (Hill et al.,2003). Apart from 
that, LIDAR data like other optical remote sensing techniques 
are restricted by clouds and dense atmospheric haze. This can 
attenuate the signal before it reaches the ground. Another 
limitation of LiDAR is the lack of algorithms and data 
processing expertise required for operational use of the data. All 
these enhance the integration of this data with other satellite 
system. 
An interesting new development is the combination of airborne 
LiDAR with terrestrial LiDAR for forestry and the creation of 
virtual forest environments. (Evans, 2003). Off shore tidal area 
are anther important application area. A LiDAR survey has 
been done for Willapa Bay in Washington, USA, demonstrating 
the utility of the technique in intertidal areas. 
13.4 Engineering applications 
LiDAR has been used for engineering work such as railways, 
powerlines and highways because of its high vertical accuracy 
and the density of points. The application for power lines, 
(Silver, 2001) and the ability to accurately determine the 
position of the cables is an excellent indication of the usefulness 
of LiDAR. 
When a camera is flown with the LiDAR, even if a non metric 
camera, then large scale mapping can be carried out. Figure 7 
shows a plot of a highway intersection with detail and contours. 
Compiled from the LIDAR DEM and a digital image acquired 
at the same time as the LiDAR data. 
The use of LiDAR for the generation of 3D city models is well 
established and some techniques are discussed in section 13.5. 
High density point clouds can be used to extract buildings and 
roof detail by fitting planes to the points. TerraScan provides 
tools for creating fully dimensional vectorised models of 
buildings from LiDAR data based on identification of planar 
roof surfaces. Chayakula (2004) has investigated the use of 
airborne IfSAR in urban areas and shown that useful 
information can be extracted. Houshmand and Gamba (2001) 
have also worked on this topic (see below).