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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008
Note that the congestus clouds were masked due to the lack of
the information of water content of such clouds and geometrical
depth of the clouds.
QFE (uncorrected from height effects) was used to estimate the
air pressure error. As the wind speed low and the area of interest
were not so much vast, a central station was chosen to derive
the air pressure. Another station was used to validate the
amounts. Air pressure amounts were assumes like Table2 and
exracted from Mashhad Meteorological synoptic data.
Parameter
12-09-2005
08-08-2005
Air Pressure (mb)
903.2
894.6
Table 2: QFE amounts of images.
Air pressure zenith delay was calculated from equation 4.
For each pixel, the amount of error was extracted by nearest
neighbor interpolation of error map and 0 was calculated by
using the SLC header parameters like near range and height.
After implementing the error algorithm, plane fit strategy was
chosen to flatten the interferogram. Final Corrected
interferogram could be seen in Figure 5.
ZHD = 10 -6 — P s
§ m
(3)
Where g m is the local gravity at centre of atmospheric column.
As could be seen, by using the values of Table 2 around 2
centimeter error was derived which is too much high. If a plane
fit algorithm is used for flattening this error will be almost
removed. But if a calculative method is implemented, this error
may be ruined the results.
The total error map is shown in Figure 4.
To implement this map to the interferogram, the Eq.4 was used
(Zebkeretal, 1997).
4tt ZTD
 Cos 6'
(4)
In this equation, ZTD is the Zenith total delay and 0 is the
incident angle at each point. A point to point algorithm was
implemented to th interferogram for total atmospheric
correction.
Figure5: Corrected and flattened interferogram
4. RESULTS
GPS time series points were used in this stage to validate the
results. 3 points in approximately middle parts of this
interferogram and near the subsidence area (where is the
research area of interest) was used for this purpose. The
distance between the points is around 20 kilometers. The
comparison of the values could be seen in Table 3. (The GPS
values were obtained from the National Cartographic centre of
Iran). The uncertainty of GPS values are around a millimeter.
The total RMS Error of these points is around 8.6 Millimeters
which is acceptable in comparison with the other carried out
activities.
Points
InSAR (mm)
GPS (mm)
Mashhad
-8
-2
Tous
-52
-41
Torqabeh
5
-3
Table 3: GPS and InSAR deformation
Figure4: Total Error map
5. CONCLUSION
As it could be seen in validation part and the result map, the
atmospheric artifacts was reduced in the correction process. The
RMS error of just flattened interferogram was about 1.9
centimeter. Furthermore if the water vapor amounts differed
more in location, this error would be intensified.
Implementing the flattening model after atmospheric correction
helps the process to obtain better results. By using the flattening
model before the correction, some unreal systematic error
would be imported to the interferogram; because the specific
model which used for flattening will omit the linear errors and
linear parts of other influences. This would cause overreduction
on the interferogram. Mitigating the air pressure, implementing
the total error map to the interferogram and flattening in respect
showed around 9.1 millimeters disagreement between InSAR
and GPS. This shows that the linear errors like Ionosphere could
be neglected if a fit method for flattening was chosen.