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International Archives of the Photogrammetry, Remote Sensin 
g and Spatial Information Sciences, Volume XXXIX-B4, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
was obtained prior to the disaster, then quantified changed 
volume for the damaged area (Sohn et al., 2011). 
   
    
    
Leica 
Scanstation 2 
Trimble GX 
Figure 4. Terrestrial LiDAR scanner 
Trimbie CX 
4. EXPERIMENTAL RESULT 
41 Study Area 
Mt. Umyeon is located on a central region of Seoul and 
surrounded by urban facilities. Analysis results from a forest 
map produced by Korea Forest Service showed that most forest 
types around Mt. Umyeon were the deciduous and the mixed 
stand forest and over 30 years old tree reached 97% nearly. A 
natural ecological park with a small-size reservoir was 
developed at the southern area of Mt. Umyeon. Around Mt. 
Umyeon, there was no district zone designated as a disaster risk. 
  
  
  
  
Legend 
  
© CNES 2011 Landslide area 
  
T T 
  
? 
x: m "AVE 
Figure 5. Location of Study Area (Mt. Umyeon) 
42 Multi-sensor Data Processing for Damage Analysis 
In order to extract the damaged extent, pre- and post- aerial 
photos, a variety of digital map from NDMS (National Disaster 
Management System) Database, and the Optic and SAR images 
from International Charter were utilized in this study. 
Simultaneously, point clouds of the landslide area were 
collected and processed through the terrestrial and the aerial 
LIDAR, For damage extent extraction caused by landslide and 
flood for the study area, collected pre- and post-disaster 
Imagery were used as an experimental data to apply for image 
algebra change detection algorithm (John, 1996). 
20 = Vy Jd y Slain S (1) 
Where, 
Di; = change pixel value 
Z1 brightness pixel value at time 1 
S20 = brightness pixel value at time 2 
c — constant 
The total landslide extent of three damaged regions (red collar 
polygons on Figure 6) in the study area estimated by change 
detection algorithm was about 8.6 ha. 
3T 29H 
Y anon 
TWH 
            
  
WE £ 
Figure 6. Extraction of damage are 
a by landslide 
Aerial photos from the small manned helicopter and Unmanned 
Aerial Vehicle were conducted by post-processing procedure. 
For geometric correction and rectification of aerial images 
through an aerial triangulation (AT), Ground Control Points 
(GCPs) were extracted from 1/1,000 scale digital map produced 
at National Geographic Information Institute (NGII). After 
Aerial triangulation processing, the digital terrain model with 
Im spatial resolution and 5cm-level ortho-rectified photos were 
generated. Final mosaicked ortho-imagery was made using 
DTM data and ten ortho-rectified photos with an accuracy of 
1.45m (RMSE). 
  
Figure 7. Ortho-rectified photos (left) and aerial LiDAR by 
RAMS (right) 
Before terrestrial LiDAR scanning, Ground Control Points 
(GCPs) survey was carried out using static GPS method as 
setting up eight control points around the landslide and the 
reservoir's bank collapse area for almost eight hours. The data 
process of collected LiDAR point clouds was performed as 
following; point cloud geo-referencing and registration, outlier 
eliminating, 3D mesh/surface generating and editing, DTM 
generating, and 3D modelling of the study area. 
311