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New perspectives to save cultural heritage
Altan, M. Orhan

P. Boccardo J ‘ , E. Borgogno Mondino a , F. Giulio Tonolo a
a Politecnico di Torino - Dipartimento di Georisorse e Territorio
C.so Duca degli Abruzzi, 24- 10129 Torino - ITALY
Piero.boccardo@polito.it; enrico.borgogno@polito.it; fabio.giuliotonolo@polito.it
KEY WORDS: Satellite remote sensing, Orthorectification, Mapping, Land cover, Rational Function Model, Pan-sharpening,
Classification, High resolution
The availability and variety of high resolution satellite images (Eros, QuickBird, Ikonos, Spot5 supermode) have led us to consider
the possibility of updating middle scale cartography. This paper presents a methodology to produce accurate orthocorrected images
which can be used to generate updated maps at a scale of 1:10000. Even though commercial software already allow such operations
to be made, we have implemented an alghorithm that is based on the RFM (Rational Function Model) in order to control the
positioning errors and the influence of the ground control point distribution on the results. Such an approach also permits us to
investigate whether any of the 78 RPCs (Rational Polynomial Coefficients) are negligible. We assume that a DEM (Digital Elevation
Model) of the investigated area is available (e.g. from SAR interferometry, SPOT5 mission,...). In order to define the maximum
obtainable map scale (which depends on the geometric resolution of satellite images and on the adopted sensor model) accuracy tests
have been carried out using a reasonable number of check points: the results are presented in this paper. The spectral information
from multispectral data (XS, with a lower geometric resolution than the panchromatic band, PAN) can be used to produce thematic
maps which can be considered as an added value of the process, especially in sites of cultural value. A Pan-Sharpening algorithm has
been implemented paying particular attention to the file size management (through a partitional approach) and the corrispondences
between PAN and XS spectral ranges. An example of a land cover map that was produced through a neural classification of such
orthocorrected images is presented.
Cultural site investigations require updated middle scale
cartography to refer to. High resolution satellite images could
be succesfully used to face such needs, but orthoprojection has
to be taken into consideration. In literature remotely sensed
satellite images have been orthocorrected using both rigorous
sensor models and general non parametric models.
1.1 The Rigorous Sensor Model
Rigorous sensor models are based on collinearity equations;
each line of the image, but not the entire image, can be
considered a central perspective. Collinearity equations have to
be modified to take into consideration the time dependence of
the sensor’s attitude and position. Starting values can be
obtained from ancillary data, provided with images, by the
reseller company: the position vectors, attitude values and the
starting/end times of acquisition are usually provided.
Otherwise, the starting values have to be calculated using linear
models (i.e. time dependent linear transformed DLT equation).
A rigorous sensor model is often not available; this means that
general projecting (non parametric) algorithms have to be used.
1.2 The Rational Function Model
One of the most commonly used non parametric models is the
Rational Function Model (RFM). This model, proposed by
OPENGIS consortium relates the image coordinates (>,0) and
the three dimensional terrain coordinates {X, Y,Z) through a ratio
of the 3 rd order (maximum) polynomials (20 coefficients), as
P h (X,Y,Z)
P C (X,Y,Z)
These equations are called RFM upward equations. It can be
useful to calculate the terrain coordinates from the knowledge
of the image coordinates and of the Z values, according to the
following equations, which are known as RFM downward
x P&,ri,Z)
P b (4,V,Z)
y P&.TI.Z)
In order to correctly estimate polynomial coefficients it is
necessary to collect a sufficient number of Ground Control
Points, ranging from a minimum of 7 (1 st order polynomial) to a
maximum of 39 (3 rd order polynomial), considering that the first
coeffincient in the denominators is assumed to be equal to 1.
Both the rigorous and the non parametric models are available
in commercial software. A non parametric approach, which is
based on a self developed RFM alghoritm (IDL programming
language), is shown in this paper. The self developed
alghorithm permits us to keep the behaviour of such a
methodology under control.