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

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