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Figure 4. Ground projection of the orbits 
3. DEPTH EXTRACTION 
In order to extract the depth information from the imagery we 
used the Jupp method as described in Green et al. (2000). The 
algorithm was implemented by the authors in IDL language and 
integrated in the ENVI software. The 5419 image was pre 
processed according to the procedure described in Deidda et al 
(2012). This procedure divides the image in classes each 
corresponding to different homogeneous bottom type. Among 
the classes thus identified, we selected the one corresponding to 
the sand bottom. This class was represented as a ROI (region of 
interest) in the ENVI software. We used a coordinate 
transformation to transport the sand class from the 5419 to the 
5318 image, avoiding this way to change the radiance values of 
the pixels due to georeference interpolation. A traditional 
bathymetric survey is necessary for the calibrate the method. 
The DOP zones calculated for the sand bottom class, being 
parallel to the coastline, were crossed with transverse survey 
lines, separated about 20 m from each other. The first band, up 
to a depth of about 1.50 m, was surveyed with GPS equipment 
in RTK mode, by two operators who walked along the survey 
lines. The Jupp model was applied 10 times on each image, 
once for each selected calibration area. However, not all 
calibration areas produced valid depth results, and thus some 
were discarded. In particular, for the 5419 image, the calibration 
area 1 was discarded because the produced values were 
extrapolated rather than interpolated; and areas 4, 5 and 8 which 
produced a very low number of depth values. For the same 
reason the areas 2, 5 and 9 for the image 5318 were discarded. 
Areas 6 and 10 were not used because they produced DOP 
zones which did not overlap the NRTK survey, which covered 
only part of the littoral. In Figure 5 the extension of the survey 
is shown in red, and the position of the depth values produced 
from the 5419 image (using the calibration area 7) in green.In 
order to distinguish between the depth model obtained by direct 
survey and the one calculated with the Jupp method for each 
calibration area, from now on the latter will be referred to as 
Digital Sea Bottom Model (DSBM). 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
    
Figure 5. GPS survey (red) and DSBM (green) 
4. ANALYSIS 
Our bathymetry extraction software has produced 6 DSBMs for 
the image 5419 and 7 for the 5318, each corresponding to a 
different calibration area (see Figure land Figure 2). A direct 
comparison of the models is not feasible because, due the 
different calibrations, the points where depth is estimated are 
not the same (different DOP zones). The strategy used for 
comparison was thus to spatially intersect the models and limit 
the comparison to the common areas. The comparison with the 
NRTK survey of the bottom, which preceded the one between 
the DSBMs, also required the choice of a criterion to match the 
points to be compared. In this case, the comparison was made 
between the surveyed depth and the closest point of the 
extracted model, up to a distance of one half pixel (1.2 m on the 
terrain). 
4.1 Image 5419 
  
  
  
  
  
Calibration — Average Standard 
area (m) deviation (m) 
2 0.25 0.21 
3 0.30 0.20 
6 0.21 0.20 
7 0.21 0.19 
9 0.39] 0.22} 
10 0.46] 0.26| 
  
  
  
  
  
Table 3: Averages and standard deviations of the differences 
between the points of the DSBM and those of the NRTK survey 
for the seven calibration areas of the 5419 image. 
Calibration areas 9 and 10 were discarded because the average 
differences are too high.