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Additionally, an ortho-image was produced using the extracted 
DEM. Processing of the ASTER data was relatively 
straightforward compared to the archive imagery. 
For the photogrammetric processing (interior, exterior, and 
absolute orientation) of the USGS aerial imagery, BAE Systems 
SOCET SET 5.5.0 was used. For automated DEM extraction the 
SOCET SET NGATE module was used. Individual frames and 
image blocks for each site were processed using the multi- 
sensor triangulation (MST) module within SOCET SET. The 
interior orientation of the USGS imagery is not trivial as 
fiducial mark coordinates were not available. However, the 
focal length and lens distortion parameters were known. The 
radial lens distortion parameters for the two Metrogon USGS 
camera lenses pertaining to the selected imagery are detailed in 
Spriggs (1966) and plotted graphically in Figure 2. The USGS 
frames contain four observable fiducial marks in the centre of 
each image side. For their reconstruction the image coordinates 
for each fiducial mark were measured using Adobe PhotoShop 
CS2 and the centre of the image was determined as the 
intersection between lines of opposing fiducial marks. The 
principle point was assumed to be located at (0,0) and the 
calculated intersection point gave the respective offsets to 
reduce the fiducial mark coordinates. The final fiducial marks 
coordinates were then calculated as the average of the reduced 
fiducial marks. The described lack of calibration information is 
not uncommon in studies that include archive imagery. The 
work-around as described here has been successfully adopted in 
other studies (Miller et al, 2007; Fox and Czifersky, 2008; 
Dornbusch et al, 2010). A new camera calibration file was 
created and the final interior orientation RMS was within 0.5 
pixel. 
  
0.15 % T T T 
| — T11 DS2294 
: T11 RF4224 
   
0.05 F 
  
0.00 [em 
-0.05 
Displacement [mm] 
-0.10 Fr 
  
  
015k i L i 1 À i i L 3 Jj 
0 5 10 15 20 205 30 535 40 145 50 
Field angle [degrees] 
  
Figure 2: Lens distortion for the two Metrogon T11 lenses 
For the exterior orientation, at least 25, regularly distributed tie 
points per image per were measured automatically using the 
automatic tie point matching facility within SOCET SET. The 
resulting tie points were manually examined and adjusted or 
deleted if necessary. Additional points at varying elevations 
were added to strengthen the orientation solution. Distinctive 
features such as mountain ridges, rock outcrops or features on 
stable sea-ice were utilised. This produced a final exterior 
orientation RMS value of less than one pixel. 
Because no ‘true’ GCPs were available, the absolute orientation 
of the historical image strips proceeded by using information 
from the ASTER data and 2005 aerial photography. To achieve 
an approximate absolute orientation, at least six ‘artificial’ 
GCPs were extracted from the present-day ortho-imagery and 
DEMs, at the location of distinct surface features. After 
achieving a successful absolute orientation solution, TIN-based 
DEMs were extracted from the historical imagery. Point 
extraction on a grid basis was avoided because oversampling 
can occur in areas with low image contrast such as snow 
covered areas (Fox, 1997). Depending on the reference data 
accuracy, the RMS,,, values of the absolute orientation of the 
historical DEMs were within + 30 m when initiated by ASTER 
and + 10 m for the modern aerial imagery. 
  
ASTER Image {Band 3H & 3B} USGS Archive Stereo Imagery 
  
Y 1 
  
Reconstruction of interior 
DEM and Oftho-image Generation Si SEO aou oon 
  
  
  
  
  
  
  
  
  
  
i Y 
Extraction of "artificia GCPs initial absolute orientation 
from ASTER With extracted ASTER GCPs 
Relative ASTER DEM Historical DEM 
Surface Matching 
  
DEM Differencing 
  
  
  
Figure 3: Workflow of DEM production and assessment using 
ASTER imagery and historical archive stereo-photography 
without ground control. 
However, despite the successful extraction of DEMS, the initial 
fit between the historic and the modern DEMs is too poor for 
the precise measurement of volumetric glacier change. This is 
because it is only possible to extract a minimal number of 
artificial GCPs from the present-day ASTER/aerial imagery, 
and the accuracy of the extracted points is relatively low in 
comparison to that which would be achieved through field 
survey. Consequently, the absolute orientation of the archival 
imagery using these points results in only an approximate 
alignment of the datasets. To overcome this limitation and to 
correct for remaining offsets between the DEMs a robust 
surface matching technique was applied. The complete 
workflow is summarised in Figure 3. 
4. SURFACE MATCHING 
Surface matching has become an increasingly relevant 
technique in geoscience applications in recent years. A growing 
number of multi-temporal, multi-scale and multi-sensor datasets 
are now available for environmental studies concerned with 
assessing surface changes over long time periods (Mills et al.,