elevation data from the Antarctic Digital Database 
(Thomson and Cooper, 1993). 
3) A line of barometric surface elevations from a 
survey flight over an adjacent glacier were 
obtained in 1975 by BAS. These were measured 
by simultaneously recording the terrain clearance 
of the aircraft using a radar system and elevation 
from a pressure sensor. The pressure sensor 
readings were adjusted to height above sea-level 
by observing the terrain clearance when crossing 
features of known elevation, such as open sea or 
ice-shelf. 
4) A block of aerial photographs. These were 
acquired on 1 January 1991, using a Zeiss 
RMKA15/23 camera mounted in a deHavilland 
Twin Otter. The flying height was 3800 m, 
resulting in a nominal plate scale of 1:25,000. 
Additionally, satellite radar altimeter data were 
investigated. Measurements from the Geosat mission were 
available for the region, but none were found in the study 
area. If such data had been available, they would have 
been of great use, superseding the barometric surface 
elevations. Satellite altimeter data are only likely to be 
available for very smooth, flat regions such as snow-fields, 
because of limitations in the surface tracking systems on 
board the satellite (Rapley and others, 1983; Mcintyre, 
1991). 
METHODS 
To carry out the block adjustment of the aerial 
photography, it was necessary to provide both planimetric 
and vertical control. The survey point provides both but 
one point is inadequate to control the block. Two data 
sources were used to create extra control. In the first case, 
additional planimetric control was generated by using the 
georeferenced TM image. Points on the aerial photographs 
were identified on the satellite image, and their positions 
were determined using routines which were created within 
a GIS system. 
Vertical control was more difficult to provide. The only 
additional source of height control was from the line of 
altimetric data from an airborne survey. Unfortunately, this 
was entirely over snow-fields, which presented insufficient 
detail on the aerial photographs for stereo-matching. A 
shape-from-shading technique was used to generate a 
digital elevation model of the snow fields from the satellite 
image. This shape-from-shading technique was developed 
by APRC, and only brief details are presented here. 
Further details are available on application to the senior 
author. 
Shape-from-shading studies are based on numerical 
algorithms to solve (1), which describes the formation of an 
image from a surface with Lambertian scattering properties 
(Rouy and Tourin, 1992). 
c 
WA (1) 
"() (5) 
Ox) \oy 
where l(x,y) is the image, o, B and y are the components 
of the unit vector in the direction of illumination and x,y, 
and z are Cartesian coordinates with x and y in the 
horizontal plane and z vertical. For solar illumination, 
where the light source is very distant, the parameters o, p 
and y are constant. 
Equation 1 is difficult to solve, and under some 
circumstances may not have a unique solution. For many 
topographic surfaces, an important simplification can be 
made, i.e. for small slopes: 
EE von 
ox) \oy 
Substituting (2) into (1) gives: 
oz oz 
=0 — + {} — + 3 
Kx) ps Bs Y (3) 
As I(x,y) is arbitrarily scaled, the constant y can also be 
ignored. 
A solution to (3) can be found by taking the Fourier 
transform of the image. This results in the following 
relationships: 
-2nD ks + 2 4 
Poo, ve[ 2 e 
e Th 4 n, 5 
Qnin, baje 23 ( ) 
where p and q are the coefficients of the Fourier transform 
of the image and a and b are the coefficients of the Fourier 
transform of corresponding elevations. 
Thus, by taking the discrete Fourier transform of l(x,y) to 
obtain the coefficients p and q, the coefficients a and b can 
be obtained by applying equations 4 and 5. The surface is 
then constructed by taking the inverse Fourier transform of 
the resulting set of coefficients. 
This technique has several advantages over direct 
integration of the image. The solution is a consistent 
surface for the entire area considered, with no 
discontinuities introduced by short wavelength features. 
Because the functions in (4) and (5) constitute a low pass 
filter in the frequency domain, the result is unaffected by 
high frequency features in the image, such as crevasses. 
  
  
  
  
  
Test No. Xy ony Errors 
No. of 
points Xy z Xyz 
1 6 0 37.6 153 30.9 
2 14 5 176.4 30.4 140.0 
3 8 0 60.5 13.6 475 
4 13 5 259.2 201.8 193.0 
5 9 0 59.6 14.6 47. 
6 7 2 178.1 30.1 140.0 
7 10 1 1707 30.8 1367 
  
  
  
  
  
  
  
Table | Summary of test results 
422 
2006 — 
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2005 
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