between the DSM and the DTM is calculated to produce a 
normal heights raster image. Figure 3 a, b, and c illustrates the 
produced LiDAR raster image data (intensity, DSM, and 
Normal Height (NH), respectively). Figure 3d represents the 
ortho-rectified aerial photos for the study area. 
4. RESULTS AND DISCUSSION 
A close look to the data provided and the characteristics of the 
study area shows that the intensity values of the areas covered 
by vegetation (either trees or grass) are higher than those 
covered by man-made features (buildings and roads). This is 
expected from the reflectance characteristics of vegetation in 
Near Infra-Red range. It is also observed that the intensity of the 
areas covered by buildings and roads are more homogeneous 
than the intensity of trees and grass areas. Moreover, the tree 
areas have a larger variation in elevations compared to the 
buildings and road areas. Based on the previous observations, it 
is noted that intensity data can be effectively used for 
distinguishing man-mad features from vegetation fields. The 
texture of the intensity can be used for representing the 
homogeneity of the land covers, Figure 4 i. The slope of the 
elevation data can be used to represent the plane surfaces, such 
as buildings and roads, Figure 4 ii, and iii, for the DSM and NH 
respectively. 
AI 
|i 
5 
  
Figure 4: Bands created from range and intensity data 
1) Intensity Texture, ii) DSM slop, and iii) NH slope 
The prepared raster LIDAR data are used individually for the 
land cover classification process, Figure 5. The image data 
bands used individually are: a) Intensity, b) DSM, and c) 
Normal Height. Additionally, six combinations of image bands 
are developed to examine the use of the auxiliary data on the 
classification results. The auxiliary band combinations are: d) 
Intensity and DSM, e) Intensity and Normal Heights (NH), f) 
Intensity, DSM, and Intensity Texture, g) Intensity, NH, and 
Intensity Texture, h) Intensity, DSM, Intensity Texture, and 
    
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
    
DSM Slope, and 1) Intensity, NH, Intensity Texture, and NH 
Slope. The results of land cover classification of all cases are 
shown in Figures 5 se a to 1). 
      
Trees 
Buildings 
Grass/ Bare Soil 
Roads 
  
6) | (k) 
Figure 5: Results of Land Cover Classification 
The principal components from the 4-bands (Intensity, DSM, 
Intensity Texture, and DSM Slope) are generated and classified 
(case j). Other principle components from the Intensity, NH, 
Intensity Texture, and NH Slope are also generated in order to 
test the effect of using the normal height instead of the DSM on