1301
EXTERIOR ORIENTATION IMPROVED BY THE COPLANARITY EQUATION
AND DEM GENERATION FOR CARTOSAT-1
Pantelis Michalis and Ian Dowman
Department of Civil, Environmental and Geomatic Engineering, University College London, Gower Street,
London WC1E6BT, UK
[pmike,idowman]@ge.ucl.ac.uk
Commission I
KEYWORDS: rigorous model, rational polynomials, collinearity, coplanarity, along track satellite imagery, DEM,
ABSTRACT:
In this paper the sensor model evaluation and DEM generation for CARTOSAT-1 pan stereo data is described. The model is
tested on CARTOSAT-1 data provided under the ISPRS-ISRO Cartosat-1 Scientific Assessment Programme (C-SAP). The
data has been evaluated using the along track model which is developed in UCL, and the Rational Polynomials Coefficient
model (RPCs) model which is included in Erdas Photogrammetry Suite (EPS). A DEM is generated in EPS. However, the
most important progress that is represented in this paper is the use of the Coplanarity Equation based on the UCL sensor
model where the velocity and the rotation angles are not constant. The importance of coplanarity equation is analyzed in the
sensor modelling procedure and in DEM generation process.
1. INTRODUCTION
CARTOSAT-1 represents the third generation of Indian
remote sensing satellites. The main improvement from the
instrument point of view is the two panchromatic cameras
pointing to the earth with different angles of view. The first
one is looking at +26 deg. of nadir while the second one at -5
deg. of nadir, giving the ability of collecting along track
stereo images.
In this paper, the rigorous sensor model developed in UCL
and the RPCs model included on the Erdas Photogrammetry
Suite (EPS) are used to evaluate Cartosat images along with
DEM generation on EPS. However, the most important
progress that is represented in this paper is the use of the
Coplanarity Equation based on the UCL sensor model where
the velocity and the rotation angles are not constant. The
importance of the coplanarity equation is analyzed and
evaluated in the sensor modelling procedure and in the DEM
generation process.
2. BACKGROUND
A pushbroom image consists of sequence of ffamelets which
are independent one-dimensional images with their own
exterior orientation parameters, as the scanning effect of line
CCD scanner on the ground is due to the motion of the
satellite. In general, the pushbroom sensor model can be seen
as a sophisticated model, which should simulate
simultaneously the along track motion, that is closely related
to the satellite trajectory and the across track perspective
projection of the ffamelets. The main drawback of this
approach is that the exterior orientation parameters of
neighbouring framelets are highly correlated.
The across track perspective could be represented with the
well known collinearity equations which should be modified
in a way that the satellite orbit is taken into consideration.
The way that the satellite motion is represented leads to
different sensor models. It is possible to have an even more
correlated model in the case that more parameters are used in
this procedure, than are really needed.
Moreover, especially for the along track stereo images it
sounds very attractive to establish the coplanarity equation
which could relate conjugate points of images. The coplanarity
equation establishes a geometric condition along the track
which can improve the stability of the orientation and the
accuracy of the DEM generation as the x-parallax is at this
direction (along track).
Kim (Kim, 2000) investigates the epipolar geometry of
pushbroom images based on Gugan and Dowman model
(Gugan and Dowman, 1988). In this model the position and
kappa rotations are described by second order polynomials
while the omega and phi rotations are constant. It is reported
that the coplanarity in pushbroom is different than in frame
cameras represented by epipolar curves instead of lines.
However the most important conclusion is that for any two
conjugate points the epipolar curves are different from each
other, as the coefficients of the coplanarity equation that was
developed are varied for each point.
Habib (Habib et al., 2005) represents a comprehensive analysis
of the epipolar geometry for pushbroom scanners moving with
constant velocity and attitude trying to produce epipolar lines
(not curves) and normalized images. It is confirmed that for a
given point in the left image, there will be multiple epipolar
planes in the right image. It is mentioned that the key
difference between frame and line cameras is that the base
vector will change as the scanner moves along its trajectory.
Finally, it is concluded that even in that simplified case
(constant velocity and attitude) the production of normalized
images are not feasible without having a DEM since the
normalized and original images do not share the same exposure
station.