The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
Time (year) 
(b) 
Figure 4. Temporal variation of atmospheric (ATM) delay in LOS direction, nonlinear subsidence (NLS) and total subsidence (TS) 
at two PS points as marked in Figure 2. (a): for P) and (b) for P 2 . 
5. CONCLUSIONS 
Combining merits of both PS and SBAS technique, this paper 
presents a PS-networking approach to map ground deformation 
with time series of SAR images. Data modelling and parameter 
(e.g., deformation velocity) estimating by function optimization 
and LS solution rely on the freely-connected network that may 
mitigate the negative impacts of both decorrelation noise and 
atmospheric delay. In terms of reliability, such FCN is more 
advantageous than the TIN applied elsewhere. Both SVD and 
EMD tool can be successively employed to reasonably isolate 
nonlinear deformation from atmospheric delay. For algorithm 
validation, some experiments have been performed to analyze 
historical evolution of subsidence in Phoenix with 39 ERS SAR 
images. The testing results show that such PS-networking 
approach is viable and efficient for detecting of the temporal 
behaviour of ground deformations. 
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ACKNOWLEDGEMENTS 
The work presented here was partially supported by two grants 
from the National Natural Science Foundation of China (Project 
No. 40774004, 40374003). The research was performed while 
the first author was a visitor to Dr. S. M. Buckley at Centre for 
Space Research, The University of Texas at Austin. The authors 
would like to thank ESA and USGS for providing radar data 
and SRTM DEM, respectively, as well as the Delft University 
of Technology for providing the precise orbital data. They also 
thank Mr. D. Yang for his assistance on SAR data processing. 
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