Even more than ten years passed after the reclamation completion in 1997, the residual settlement is still a critical issue
for the Chok Lap Kok Airport, Hong Kong. In this research, the main goal was to investigate this differential settlement
across the airport platform by using the PSInSAR-derived deformation measurement and local geological data. An
enhanced PSInSAR approach (the CPTA analysis) was applied to a total of 20 ENVISAT ASAR images acquired
between March 2003 and March 2008 for the deformation filed retrieval. Our results show that most of buildings are
stable but some of reclamation areas have still experienced a slight settlement. The results also suggest that the CPTA
approach has a potential to monitor the deformation of some special civil utilities (e.g. airfield). A statistic analysis with
the geological data indicates that the variability of residual settlement across the reclamation may be associated
reclamation fill (fill types and thickness) and geological conditions underlying the airport platform.
The main problems, temporal and geometrical decorrelation, atmospheric signal, limited the analysis and interpretation
of Differential SAR (D-InSAR) interferometric signal. The Permanent Scatterers (PS) Technique which can detect
discrete and temporarily stable natural reflectors using at least 25 images was developed shortly after. However, for
some regions, there are not enough available archived SAR images. The Stacking D-InSAR technique, using a stack of
SAR images (<20scenes), with the generated a set of unwrapped differential interferograms, can estimate the linear
differential phase rate. This research employs 6 ENVISAT ASAR images to study the ground deformation in The Pearl
River Delta region with Stacking D-INSAR technique. Obvious ground subsidence trend is found around Guang Zhou,
Fo Shan and Dong Guan where the urbanization process was very fast in the past 20 years. In order to validate the
stacking result, Persistent Scatterer technique with limited images is also applied. From the deformation velocity map
obtained by stacking technique, it is found the deformation velocity rate at some places seems higher. The main reason is
probably the presence of atmospheric artifacts. The deformation trend shown in both Stacking technique and the
Persistent Scatterer technique result are consistent in Haizhu district and Yuexiu district in Guangzhou.
This paper proposes a new ship detection algorithm based on Alpha-stable model for detection ships in the spaceborne
synthetic aperture radar (SAR) images. The current operational ship detection algorithm is based on Constant False
Alarm Rate (CFAR) method. The major shortcoming of this method is that it requires an appropriate model to describe
statistical characteristic of background clutter. For multilook SAR images, the Gaussian model can be used. However,
the Gaussian model is only valid when several radar looks are averaged. As sea clutter in SAR images shows spiky or
heavy-tailed characteristics, the Gaussian model often fails to describe background sea clutter. In this study, we replace
Gaussian model with Alpha-stable model, which is widely used in the application of impulsive or spiky signal
processing, to describe the background sea clutter in SAR images. Similar to the typical Two-parameter CFAR algorithm
based on Gaussian distribution, we move a set of local windows through the image and finds bright pixels that are
statistically different than the surrounding sea clutter. Several RADARSAT-1 images are used to validate this
Alpha-stable model based algorithm. The experimental results show improvements of using Alpha-stable model over the
Gaussian model.
In this paper, a new approach for unsupervised change-detection using multitemporal InSAR data is proposed, of which the significant characteristics is joint use of backscattering temporal intensity and long-term coherence based on 2-D (two dimensional) Renyi's entropy. The proposed approach is made up of two steps: feature extraction and unsupervised 2-D thresholding. In the first step, two features are based on the concepts of backscattering intensity variation and long-term coherence variation respectively, and are defined according to the analysis of different signal behavior of interferometric SAR in the presence of land-cover classes within urban area. In the second step, an unsupervised 2-D thresholding technique based on maximum 2-D Renyi's entropy criterion is developed. The thresholding is performed on the two difference images derived from the two features to produce an accurate change-detection map with two classes: changed and no-changed. Primary experimental results, which were obtained from a set of six multitemporal ERS-1/2 SAR images within Shanghai city of China, show the effective of the proposed approach and that ERS-1/2 InSAR data could be exploited for detecting urban land-cover changes.
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