Full text: Proceedings, XXth congress (Part 2)

stanbul 2004 
Left image: 
coded mean 
1perposed to 
een already 
] Crosetto et 
s an area of 
cending and 
independent 
wo datasets 
| include 14 
ns. The two 
orthoimage 
y notice that 
re are small 
ainly due to 
quantitative 
asetto et al. 
between the 
number of 
he obtained 
step in the 
ation of its 
oming from 
leformation 
with that of 
lity, which 
d DInSAR 
| with three 
technique: 
on. and the 
or the ERS 
  
- onal Archives i P E fry 2 20 Spicy : 2 > E VV / 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B2. Istanbul 2004 
satellites cover the last 12 years. In this paper, the most 
relevant aspects of a flexible DInSAR procedure for 
deformation measurement have been discussed. The 
procedure works with multiple interferograms over the same 
scene, i.e. with stacks of SAR images. This represents the 
key factor to achieve quantitative DInSAR deformation 
monitoring capabilities. Three main aspects of the procedure 
have been discussed. Firstly, the interferometric procedures 
to process SAR image stacks, which include a phase 
unwrapping algorithm that works on irregular networks of 
sparse pixels. With this algorithm, only the pixels that 
remain coherent over the observation period (say, few years) 
arc used. This limits the deformation monitoring to the areas 
that remain coherent over long periods, like the urban, 
suburban and industrial areas. Secondly, the least squares 
adjustment employed to estimate the deformations has been 
illustrated. The estimation strategy has been described, 
detailing few important aspects of the modelling of the phase 
components, like the residual topographic component and 
the atmospheric contribution. Thirdly, the DInSAR 
geometric aspects have been addressed, emphasizing the 
importance of the geometric model, which connects the SAR 
image space to the object space. This model plays a key role 
in the geocoding of the DInSAR products. A rigorous SAR 
model has been briefly described. In our procedure an 
accurate geometric model is achieved by refining the model 
parameters by LS adjustment using GCPs. 
Two applications based on the proposed DInSAR procedure 
have been described. The first one is a screening analysis, 
whose main goal is the detection of unknown subsidence 
phenomena using a limited set of SAR images. The second 
one is a quantitative analysis of a urban subsidence of small 
spatial extent. Without any a priori information on the 
analysed area, which has an extension of 340 kn, using 10 
ascending interferograms, different deformation areas have 
been detected. This result shows the great potential of the 
technique to perform a fast and low-cost deformation 
analysis over large areas. The analysis of the subsidence of 
small spatial extent has been based on two independent SAR 
datasets. Despite the relatively reduced number of available 
observations (13 and 14 interferograms for the ascending 
and descending dataset, respectively), the two derived 
velocity fields are very consistent, both in terms of shape 
and magnitude of the estimated deformations. This confirms 
the capability of DInSAR to quantitatively assess 
deformation phenomena, and opens the possibility to exploit 
this technique in different applications and operational 
contexts. This is also confirmed by the great number of 
projects that are based on the DInSAR technique, see e.g. 
(Strozzi et al., 2001; and Colesanti et al., 2003). 
The main limitation of the DInSAR technique 1s that it only 
provides information on the urban and industrial areas, which 
however represent a very important type of land cover, where 
most of the economical and social activities are concentrated. 
The capabilities of the procedure described in this paper will 
be improved in the future. A first step will be the joint 
estimation of the deformations by fusion of the ascending and 
descending datasets. A further step will include advanced 3D 
modelling tools to separate the deformation phase component 
from the atmospheric contribution. 
ACKNOWLEDGMENTS 
This work has been partially supported by the Spanish 
Ministry of Science and Technology, through the research 
project REN2003-00742. The author is greatly indebted to 
169 
Prof. Bruno Crippa. from the University of Milan, for his 
continuous support and fundamental help during this work. 
REFERENCES 
Amcluns F. Galloway D.L. Bell JW. Zebker LA. 
Laczniak R.f, 1999, Sensing the ups and downs of Las 
Vegas: InSAR reveals structural control of land subsidence 
and aquifer-system deformation. Geologv, Vol. 27. No. 6, 
pp. 483-486. 
Amelung F. Jonson 5, Zebker HA. Segall P., 2000. 
Widespread uplift and 'trapdoor' faulting on Galápagos 
volcanoes observed with radar interferometry. Nature, Vol. 
407, pp. 993-996. 
Baarda W., 1968. A testing procedure for use in geodetic 
networks. Netherlands Geodetic Commission, Publications 
on Geodesy, Vol. 2, No. 5, Delft (Holland). 
Carnec C., Massonnet D., King C., 1996. Two examples of 
the use of SAR interferometry on displacement fields of 
small spatial extent. Geophysical Research Letters, Vol. 
23, No. 24, pp. 3579-3582. 
Colesanti :Cir Ferretti. A: Prati €, Rocca F, 2003. 
Monitoring landslides and tectonic motions with the 
Permanent Scatterers Technique. Engineering Geology, 
Vol. 68, pp. 3-14. 
Costantini M., Farina, A., Zirilli F., 1999. A fast phase 
unwrapping algorithm for SAR interferometry. /EEE 
Transactions on Geoscience and Remote Sensing, Vol. 37, 
No. l, pp. 452-460. 
Crosetto M., Tscherning C., Crippa B., Castillo M., 2002. 
Subsidence monitoring using SAR interferometry: 
reduction of the atmospheric effects using stochastic 
filtering. Geophysical Research Letters, Vol. 29, No. 9, pp. 
26-29. 
Crosetto M., Castillo M., Arbiol R., 2003. Urban subsidence 
monitoring using radar interferometry: Algorithms and 
validation. Photogrammetric engineering and remote 
sensing, Vol. 69, No. 7, pp. 775-783. 
Crosetto M., Biescas E., Fernández L, Torrobella L, Crippa 
B., 2003b. Deformation control using SAR interferometry: 
quantitative aspects. Proceedings of Fringe 2003, ESA, 2-5 
September 2003, Frascati (Italy). 
Ferretti A., Prati C., Rocca F., 2000. Nonlinear subsidence 
rate estimation using permanent scatterers in differential 
SAR interferometry. [EEE Transactions on Geoscience 
and Remote Sensing, Vol. 38, No. 5, pp. 2202-2212. 
Ferretti A., Prati C., Rocca F., 2001. Permanent scatterers in 
SAR interferometry. [EEE Transactions on Geoscience 
and Remote Sensing, Vol. 39, No. 1, pp. 8-20. 
Goldstein R.M., Englehardt H., Kamb B., Frolich RM, 
1993. Satellite radar interferometry for monitoring ice 
sheet motion: application to an Antarctic ice stream. 
Science, Vol. 262, pp. 1525-1530. 
Hanssen R., 2001. Radar interferometry. Kluwer Academic 
Publishers, Dordrecht (The Netherlands). 
Massonnet D., Rossi M., Carmona C., Adragna F., Peltzer G., 
Felgl K., Rabaute T., 1993. The displacement field of the 
Landers earthquake mapped by radar interferometry. 
Nature, Vol. 364, pp.138-142. 
Strozzi T... Wegmuller U., Tosi L., Bitelli G., Spreckels V., 
2001. Land subsidence monitoring with differential SAR 
interferometry. Photogrammetric engineering and remote 
sensing, Vol. 67, No. 11, pp. 1261-1270. 
Rosen P.A., Hensley S., Joughin LR., Li F.K., Madsen S.N., 
Rodríguez E.. Goldstein R.M., 2000. Syntheuc Aperture 
Radar Interferometry. Proceedings of the IEEE, Vol. 88, 
No. 3, pp. 333-382. 
  
  
  
  
 
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.