ISPRS Commission III, Vol.34, Part 3A , Photogrammetric Computer Vision*, Graz, 2002
The consequence is that GCPs will always be required in order
to precisely orient images with pixel accuracy.
SAR images have a significant advantage over optical images.
Due to the image generation process, based on distance
measurements, image orientation is independent from sensor
attitude angles (Renouard and Perlant, 1993). Provided that an
accurate orbit is available, together with precise SAR
processing parameters, images are already precisely oriented
and GCPs are not required. That is the case of ERS SAR
imagery, which have a geo-location accuracy of 10 m (Mohr
and Madsen, 2001).
Mixed sensor image pairs, composed by a SAR and an optical
image, provide a strong parallax effect from where heights can
be determined (Raggam et al., 1994, Toutin, 2000). Provided
that precise orientation is known for both images, heights of
conjugate points can be determined by applying an intersection
algorithm. If only the approximate orientation is known for
SPOT then parallaxes will be systematically affected.
The essential point of the methodology proposed here for the
improvement of SPOT image orientation is that using altimetric
ground control points, the relation between parallaxes and
heights can be calibrated, allowing for the determination of
heights for a set of SAR-SPOT tie points. Using the precise
SAR image orientation and the heights of the tie-points,
planimetric coordinates can be calculated, thus transforming the
SAR-SPOT tie points into actual GCPs. These GCPs can then
be used in the standard SPOT image orientation procedure.
1.2 Study area and available data
The methodology proposed in this paper was tested with a
SPOT and a SAR scene of Portugal. The area is mountainous,
with a height range of 1000 m.
The SPOT scene is of panchromatic mode, with an incidence
angle of 25.5? to west of the trajectory. It was acquired in
August 1991, by SPOTI.
A Radarsat image, covering almost all of the area, was
available. It is of the standard mode, with a pixel size of 12.5 m
and was acquired in August 1997, in the ascending pass of the
orbit, with an incidence angle of 44°. Figure 1 represents the
location of the two images.
SPAIN
41°} j pepe
/ | PORTUGAL
Figure 1 — Location of the Radarsat and SPOT images used
An ERS-2 image of northern Portugal was also available but
with a very small overlap with the SPOT image. An ERS SAR
image would have been preferable, due to the better geolocation
information. For Radarsat, the orbit accuracy is known to be of
the order of 100 m (Rufenacht et al, 1997).
The verification of SAR image orientation was done with digital
topographic map data. A hydrographic network, digitised from
topographic maps of scale 1:25,000, was used. A set of 13
check-points uniformly distributed on the image were surveyed
with GPS and used to assess the SPOT image orientation.
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2. SPOT IMAGE ORIENTATION
2.1 SPOT sensor model
Optical line scanners on board of satellites acquire strips of
images composed of consecutive image lines. Each line is
generated by a central projection, which is represented by the
co-linearity equations, as for aerial photography but with the
difference that exterior orientation parameters are functions of
time. Figure 2 represents the image formation process and the
sensor coordinate system (x,y,z).
Platform motion
Figure 2 — Image acquisition by a linear array scanner
The relation between ground and image coordinates, in a linear
sensor, is established by the co-linearity equations. A detailed
description of these equations for SPOT is given by Westin
(1990).
The exterior orientation parameters of a SPOT scene describe
the satellite trajectory and the sensor attitude, and are all
functions of time. Usually only 4 orbital parameters are
required, all corresponding to the instant of the first image line
(Gugan and Dowman, 1988, Westin, 1990). Their variations in
time are predicted by the orbital perturbation theory.
The attitude angles at the time of first image line (roll, cy, pitch,
% and yaw, kp) are also exterior orientation parameters. Their
variations in time can be predicted by the onboard
measurements of attitude variation (Westin, 1990). In this case a
total of 7 parameters are required to orientate a SPOT scene.
Other authors prefer to model the attitude variations in time by
linear or quadratic functions, introducing the derivatives of
attitude angles as additional orientation parameters. In this case
the number of parameters becomes 10 or more.
The determination of all the parameters (space resection)
requires a number of GCPs greater or equal to half the number
of parameters. In order to achieve a strong solution in the least
squares adjustment, some redundancy is required.
The number of parameters, and consequently the number of
GCPs, can be reduced if an accurate orbit is known, as in the
case of SPOT4. Anyway, the precise modelling of sensor
attitude always requires the use of accurate GCPs.
Once the precise orientation of a sensor is established, it is
possible to do object-to-image projection and image-to-object
projections. The latter requires the height of the point above the
reference ellipsoid (77). The line defined by the sensor equations
is intersected with the surface of constant height, which can be
approximated by an ellipsoid of semi-axis a--H and b+H
(Curlander, 1982):
XY dz Q)
(a-HyY (b+H)
where a and b are the semi-major axis of the reference ellipsoid.
These projections can then be expressed as (Olander, 1998):