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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004 
  
LIDAR intensity data have been processed to produce a 
georeferenced 8 bit grey scale raster. Laser data with a density 
of 4 points/m’ have been interpolated to give a 20 cm pixel 
resolution image (fig. 8), while from data with a density of 1 
points/m’ a 1 m pixel resolution image has been obtained (fig. 
  
Figure 8. Detail of laser intensity raster 20cm pixel resolution 
  
Figure 9. Detail of laser intensity raster 1m pixel resolution 
Raster images obtained from last echo, in areas covered by 
vegetation, have low intensity values of pixel because the 
strength of laser power has been lost during several multi- 
reflection of laser beam. So rasters represented only with last 
echo are not useful to identify objects or entities, but they could 
be used to evaluate the vegetative state according to the loss of 
laser power passing through the canopy. 
As the raster pixel varies according to the point density, the 
infrared image obtained from the less dense LIDAR survey 
results noisy because the dimension of footprint and the 
distance among the laser points make the raster grid size under- 
sampled. 
However, most of features are clearly recognisable, particularly 
detachment surfaces of landslides, roads and fields are clear and 
identifiable. This raster image provides a support to understand 
ground surface state. The intensity image can be seen as a 
secondary product to supplement the primary elevation models 
rather than a purely stand-alone product. 
The intensity image, thought having similarities to 
panchromatic images, does not provide the radiometric 
resolution of the satellite orthoimage that is achieved as 16 bit 
raster. 
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The raster images from laser data have been used to integrated 
the QuickBird orthoimage over that areas that are not clearly 
visible because of presence of shadows and clouds (fig. 10). 
In the QuickBird image the landslides, particularly the 
detachment surfaces, are not identifiable, while, on the contrary, 
these objects are clearly visible trough the Lidar intensity. 
Moreover the pixel size of lidar intensity image is more detailed 
than the pixel size of QuickBird image over Bracigliano area. 
So we can integrate QuickBird image with intensity lidar data 
and eliminate shadows and clouds over the areas that have to be 
studied. At present a simple overlay of the two images has been 
performed, but a procedure of fusion is under study. 
  
Figure 10. Particular of an orthoimage and overlay with the 
intensity laser data over a landslide detachment surface 
A procedure to verify the planimetric differences between the 
images is to compare the vectorials of landslides and other 
objects obtained from intensity LIDAR data and the other ones 
obtained from the different QuickBird orthoimages. 
Moreover, the vectorials that describe the shape of landslides 
obtained from digitalisation of intensity raster, can be compared 
with the contour lines that represent the same value of intensity. 
These ones derived from resampling the raster in a new grid 
composed by 64 classes of grey scale in accordance with the 
belonging to areas with the similar radiometric characteristics 
(fig.11). Particularly, around the landslide bodies these contour 
lines identify the changement of materials between the bare 
rock (sliding surface of landslide) and the undamaged soil and 
vegetation.