The coordinate system
he same point was used
1 between historical (c)
5),
images from historical
g a contemporary DTM
historical images.
geometrically correct
images can be done by
(Luman et al, 1997;
an lead to inaccurate
up to a few meters);
g landscape changes at
ying land use changes
rban areas).
ion information
it was necessary to use
alibration information.
reconnaissance aircraft
(Redweik et al., 2009).
d forms of the fiducial
at was 9x9 inches and
fiducial marks consist
mage sides and appear
r half-arrows indicates
). This reconnaissance
oblique aerial photos
etrogon lens of 6", 12"
y
cal photographs, high-
"itizing the hardcopies
1 a suitable calibration
successfully used for
hophoto production
4). For our task, the
rer was employed. To
he imagery, the prints
ution (i.e., 16 micron
ition. To evaluate and
ced by the scanning
both digital (scanned
rdcopy (contact print)
Location | N°. of | Mean Mean Expected | Computed | Expected | Computed | Sigma- | XY-RMSE Z-RMSE
images | flying base XY XY Z Z naught | on check- on check-
height distance | precision | precision | precision | precision points points
Trento 6 8000m | 1000m | 0.8m 2.5m 6m 13m 6.5px | 235m 10m
2 7550m | 1200m | 0.8m 1.7m 5m 7m sopx |2m 7m
Rovereto 5 7550m | 1300m | 0.8 m 1.8m 5m 12m 69px | 3m 9m
Table 2: Results of acro-triangulation of historical images.
The print was digitized with the Epson Expression 1640XL
scanner and then rectified with respect to a softcopy reference
image applying a second order polynomial function. A final
RMSE of 1.25 pixel (i.e., 18.75 microns) was obtained and all
the scanned historical images were then rectified using the same
estimated polynomial correction.
3.3 Collecting 4D ground control points
As mentioned, GCPs are necessary to determine approximate
interior parameters of the historical images, e.g., by means of a
Direct Linear Transformation DLT approach (Abdel-Aziz &
Karara, 1971), and for the image triangulation phase with a
bundle block adjustment. The identification of reference points
visible in both the historical and more recent aerial images can
be very difficult, and thus often inaccurate and unreliable. Two
problems that commonly affect point or feature identification
are landscape changes and the low radiometry and resolution of
historical data (Fig. 3c and Fig. 3d). The least expensive
solution is the use of geo-referenced maps or orthoimages to
derive planimetric coordinates and DSM or trigonometric fix
points for altimetric coordinates (Redecker, 2008). The more
rigorous and reliable method consists in collecting GCPs that
are also identifiable in the historical images. In this project, a
hybrid method was used. GCPs were measured using
topographic surveying methods, collecting 20 object points
located primarily on roofs of historical buildings or edges of
monuments. To analyse the accuracy of the results, some
checkpoints were identified using the current available DSM.
3.4 Recovering the interior orientation of the images
For the transformation between pixel and photo coordinates, a
virtual coordinate system for the interior orientation was
constructed. This was accomplished by measuring the four
fiducial marks visible on a scanned image selected as reference,
assuming the geometrical centre of the marks as principle point
and origin of the coordinate system (Fig. 3b). The coordinates
of the fiducial marks with respect to the chosen principal point
were then used to compute the six-parameter affine
transformation for each digitized historical image. Moreover,
the same sensor format was ensured for all the scanned images
by cropping of a fixed image size with the principal point at its
centre. Then the DLT method was applied for assessing the
most likely nominal focal length for the flights over Trento and
Rovereto. The results confirmed that both flights were
performed with a 24" (609.6mm) focal length lens, as
previously assumed.
3.5 Recovering the exterior orientation of the image block
The block geometry of images does not guarantee a strong
camera network configuration. In this project, there was a non-
optimal block configuration because the photos came from a
single flight strip (no sidelap), sometimes with less than 60%
overlap between successive photos (Fig. 2). Moreover the use
of a tele-lens resulted in very low intersecting angles between
85
optical rays ranging in average from 10 degrees (for stereo-
images) to 16 degrees (considering three intersecting image
rays). Other researchers have shown that despite a non-optimal
block configuration, incorporating additional parameters in
triangulation can help to account for unknown geometric errors
caused mainly by the lens but also by other non-modelled
distortions (e.g, age, maintenance conditions, scanning)
(Redecker, 2008; Redweik et al., 2009). Based on this previous
work, the image orientation was performed with a standard
bundle block adjustment; however, only the exterior parameters
were solved, because the adjusted values of the interior
parameters were not statistically significant. The results of the
aero-triangulation are shown in Table 2. The expected precision
was calculated considering that the actual measurement
precision of the imagery (i.e., possibility of resolving details
and visible features, Fig. 3 c and d) is about 3-5 pixels).
Incorporating additional parameters (radial and tangential
distortions) did not produce meaningful improvements in terms
of residuals on the checkpoints.
3.6 DSM generation, ortho-rectification and mosaicking
Once the image blocks were oriented, the DSMs for Trento and
Rovereto were automatically extracted using image matching
algorithms. Different algorithms were tested, commercial and
open-source. To obtain a satisfying compromise between
smoothing effect and signal to noise relation, typical windows
of 21 x 21 pixels in rural regions and 13 x 13 pixels in urban
areas were used. As expected, the resultant surface models had
some deformations and spikes. In order to improve the quality
of the DSM, some manual editing was necessary.
To ortho-rectify and mosaic the two sets of historical images
(one for Trento and the other for Roverto), the strict
photogrammetric procedure was applied. Despite some model
distortions, the historical orthoimages overlaid on the more
recent orthoimages with a maximum discrepancy of few meters,
in particular in correspondence of relevant landscape
discontinuities. Historical orthoimages were also generated
using the current DTM. The differences between the images
obtained with the two different elevation models (one generated
using the historical images and the other generated from modern
DTM) were not noticeable.
4. ANALYSES OF LANDSCAPE CHANGES
To identify landscape changes, it is first necessary to identify
some features and areas of interest. Normally in urban
environments, these features are buildings, roads and
vegetation. Manual image interpretation techniques are always
more reliable although time consuming. Automatic or semi-
automatic techniques are desirable although the radiometric
quality of historical images is often not satisfactory for such
approaches. The orthoimages generated from the
reconnaissance aerial photos (WWII) were compared to the
orthoimages dating back to the 1970s and 2000s in order to
reveal changes in landscape and urban expansion that has
occurred over the past 60 years.
