ERS-1 SAR Images Research Articles

Integration of persistent scatterer interferometry and ground data for landslide monitoring: the Pianello landslide (Bovino, Southern Italy)

We present an example of integration of persistent scatterer interferometry (PSI) and in situ measurements over a landslide in the Bovino hilltop town, in Southern Italy. First, a wide-area analysis of PSI data, derived from legacy ERS and ENVISAT SAR image time series, highlighted the presence of ongoing surface displacements over the known limits of the Pianello landslide, located at the outskirts of the Bovino municipality, in the periods 1995–1999 and 2003–2008, respectively. This prompted local authorities to install borehole inclinometers on suitable locations. Ground data collected by these sensors during the following years were then compared and integrated with more recent PSI data from a series of Sentinel-1 images, acquired from March 2014 to October 2016. The integration allows sketching a consistent qualitative model of the landslide spatial and subsurface structure, leading to a coherent interpretation of remotely sensed and ground measurements. The results were possible thanks to the synergistic operation of local authorities and remote sensing specialists, and could represent an example for best practices in environmental management and protection at the regional scale.

Modeling Surface Soil Moisture from Microwave Remote Sensing Data in Solani River Catchment, Uttarakhand, India

The spatiotemporal variation of surface soil moisture is a key subject variable need to be assessed accurately since it plays a crucial role in partitioning of rainfall into runoff and infiltration. Active microwave remote sensing has offered prominent potential towards accurate estimation of surface soil moisture. Present study utilizes ERS-2 SAR image for estimating surface soil moisture by incorporating the effect of topography, vegetation and surface roughness over three land cover types namely; sugarcane, wheat and barren land through Multiple Linear Regression (MLR) approach. Five independent variables considered for MLR analysis include backscatter coefficient (σ0 ), local incidence angle (αi), surface roughness height (hs), Leaf Area Index (LAI) and Plant Water Content (PWC), respectively. Results indicate retrieval of soil moisture within ± 20% accuracy for all the three land cover types with higher accuracy for barren land (i.e. R2 ~ 0.78 and RMSE = 1.31) as compared to the other two land cover types (i.e. sugarcane; R2 ~ 0.67 and RMSE = 3.60 and wheat; R2 ~ 0.72 and RMSE = 1.94). The present study reveals the effectiveness of MLR approach in the retrieval of surface soil moisture using fewer numbers of variables.

InSAR measurement of the deformation around Siling Co Lake: Inferences on the lower crust viscosity in central Tibet

AbstractThe Siling Co Lake is the largest endorheic lake in Central Tibet. Altimetric measures, combined with lake contours, show that in 1972–1999 its water level remained stable, while it increased by about 1.0 m/yr in the period 2000–2006. The increased rate gradually stepped down to 0.2 m/yr in 2007–2011. The ground motion associated with the water load increase is studied by interferometric synthetic aperture radar (InSAR) using 107 ERS and Envisat SAR images during the period 1992–2011. The deformation amplitude closely follows the lake level temporal evolution, except that subsidence continues in 2008–2011, while the lake level stagnated. This temporal evolution suggests a non elastic relaxation process taking place at a decade timescale. Phase delay maps are used to constrain possible layered viscoelastic rheological models. An elastic model could partly explain the observed subsidence rate if elastic moduli are about twice lower than those extracted from VP/VS profiles. The surface deformation pattern is also extracted by projecting the phase delay maps against the best fit model temporal behavior. It shows that deep relaxation in the asthenosphere is negligible at the decade timescale and favors the existence of a ductile channel in the deep crust above a more rigid mantle. Overall, the best fit model includes a ductile lower crust, with a viscosity of 1–3 × 1018 Pa s between 25 and 35 km and the Moho (at 65 km), overlying a rigid mantle.

Integration between ground based and satellite SAR data in landslide mapping: The San Fratello case study

The potential use of the integration of PSI (Persistent Scatterer Interferometry) and GB-InSAR (Ground-based Synthetic Aperture Radar Interferometry) for landslide hazard mitigation was evaluated for mapping and monitoring activities of the San Fratello landslide (Sicily, Italy). Intense and exceptional rainfall events are the main factors that triggered several slope movements in the study area, which is susceptible to landslides, because of its steep slopes and silty–clayey sedimentary cover.In the last three centuries, the town of San Fratello was affected by three large landslides, developed in different periods: the oldest one occurred in 1754, damaging the northeastern sector of the town; in 1922 a large landslide completely destroyed a wide area in the western hillside of the town. In this paper, the attention is focussed on the most recent landslide that occurred on 14 February 2010: in this case, the phenomenon produced the failure of a large sector of the eastern hillside, causing severe damages to buildings and infrastructures. In particular, several slow-moving rotational and translational slides occurred in the area, making it suitable to monitor ground instability through different InSAR techniques.PS-InSAR™ (permanent scatterers SAR interferometry) techniques, using ERS-1/ERS-2, ENVISAT, RADARSAT-1, and COSMO-SkyMed SAR images, were applied to analyze ground displacements during pre- and post-event phases. Moreover, during the post-event phase in March 2010, a GB-InSAR system, able to acquire data continuously every 14min, was installed collecting ground displacement maps for a period of about three years, until March 2013. Through the integration of space-borne and ground-based data sets, ground deformation velocity maps were obtained, providing a more accurate delimitation of the February 2010 landslide boundary, with respect to the carried out traditional geomorphological field survey. The integration of GB-InSAR and PSI techniques proved to be very effective in landslide mapping in the San Fratello test site, representing a valid scientific support for local authorities and decision makers during the post-emergency management.

Simulation of time-series surface deformation to validate a multi-interferogram InSAR processing technique

A refined, small baseline subset (SBAS) interferometric synthetic aperture (InSAR) method has been developed to estimate time-series surface deformation through fusion of multi-interferogram processing. Using a synthetic data set that takes into account two time-varying deformation sources, topography-induced errors, atmospheric delay anomalies, orbital errors and temporal decorrelation, all of which are based on realistic ERS-1/ERS-2 SAR image acquisition dates and baseline configuration over the Seguam volcano, Alaska, we assess the accuracy of the refined SBAS technique. Detailed comparison between SBAS-derived products, including time-series deformation maps, atmospheric delays and baseline errors with those of synthetic values, attest the robustness of the refined SBAS technique. The root mean square error of the mean deformation rate between the simulated and SBAS-retrieved is about 0.66 mm year–1. Thus, the measurement accuracy of the refined SBAS method would be around 1 mm year–1.

Vegetation effects on soil moisture estimation from ERS-2 SAR images

The aim of this study was to map soil moisture from ERS-2 SAR images by minimizing the effect of vegetation on the backscatter coefficient. Detailed analysis was carried out to identify the prominent crop descriptor (i.e. crop height, h; leaf area index, LAI; and plant water content, PWC), and to minimize its effect on soil moisture estimation. A semi-empirical water cloud model was used to eliminate the vegetation effects on the backscatter coefficient. Our results showed that the water cloud model based on LAI as the canopy descriptor was able to estimate the crop-covered backscatter coefficient more accurately than the models based on either of the other two crop descriptors. Once the crop-covered backscatter coefficient was determined, a nonlinear least square method (LSM) was implemented to estimate the volumetric soil moisture. A significantly high correlation (R2 ≈ 0.94) between the estimated soil moisture and the corresponding observed soil moisture for barren land, as well as crop-covered surfaces, was obtained. Subsequently, individual soil moisture maps were generated from the three ERS-2 SAR images to depict the spatial distribution of soil moisture during the three seasons. Editor Z.W. Kundzewicz; Associate editor J. Simunek Citation Said, S., Kothyari, U.C. and Arora, M.K., 2012. Vegetation effects on soil moisture estimation from ERS-2 SAR images. Hydrological Sciences Journal, 57 (3), 517–534.

Flood mapping of Danube River at Romania using single and multi-date ERS2-SAR images

Several flood mapping classification techniques, applied to single-date and multi-date SAR images of ERS2, based on the Danube River flooding of 2006 in Romania are compared, as part of an effort to explore the feasibility of mapping flooded areas by SAR images acquired through radar sensors. Among 7 SAR images analyzed for the same study site located around Bistret of Romania, several represent “dry” and several “wet” conditions, where the latter represent the major Danube flooding event of 2006. The images were classified into (1) permanent water (Danube River and lakes), (2) flooded area, and (3) dry land, using single image, pixel-based classification, frequency-based contextual classification, and principal component analysis (PCA) combined with Isodata classification. The flooded areas delineated from the above procedures for the study site at Bistret are visually compared with that of Landsat-TM images and MODIS mosaic and digitally compared with referenced flooded area produced by the DEM data of SRTM. Apparently there is no one technique that is clearly better partly because of the nature of SAR data (radar echoes) and partly because of data noise even though the images were first subjected to speckle filtering and geometric corrections, and partly because SAR images could appear dark not only because of flooding but also because of smooth surfaces, target sizes, etc. However, if multi-date SAR images of both DRY and WET (flooding) conditions are available, it seems that PCA combined with the Isodata classifier would give better defined flooded areas of the Danube River than the simple single image, pixel-based classification or the contextual classification.

Dynamics of tidewater surge-type glaciers in northwest Svalbard

AbstractThe evolution of ice dynamics through surges of four tidewater-terminating glaciers in northwest Svalbard is investigated by remote sensing. A 20 year time series of glacier surface flow speeds and frontal positions is presented covering the recent surges of Monacobreen, Comfortlessbreen, Blomstrandbreen and Fjortende Julibreen. Surface flow speeds were derived using feature tracking between pairs of ERS SAR and ALOS PALSAR images, while frontal positions were taken from the same imagery, as well as more frequent but lower-spatial-resolution Envisat Wide Swath Mode images. During all four surges, increased ice flow caused the tidewater margin to advance while the calving flux was initially reduced to near zero due to compressive stresses limiting crevasse propagation. As ice speed decreased, the terminus continued to advance, until the glacier’s speed had returned to its pre-surge flow rate. Only at this time did the terminus start to retreat and peak iceberg calving flux was established. We conclude that terminus advance closely tracks glacier speed-up, that there is little mass loss through calving during the most active phase of the surge, and that seasonal cycles of terminus positions diminish during the active surge phase.

The impact of uncertainty in satellite data on the assessment of flood inundation models

► Uncertainty in observed data can influence the assessment of model performance. ► The assessment of model performance using spatial pattern comparisons should be avoided where possible. ► A probabilistic treatment of observed data should be used to gain a more holistic understanding of flood risk. The performance of flood inundation models is often assessed using satellite observed data; however, these data have inherent uncertainty. In this study we determine the patterns of uncertainty in an ERS-2 SAR image of flooding on the River Dee, UK and, using LISFLOOD-FP, evaluate how this uncertainty can influence the assessment of flood inundation model performance. The flood outline is intersected with high resolution LiDAR topographic data to extract water levels at the flood margin, and to estimate patterns of uncertainty the gauged water levels are used to create a reference water surface slope for comparison with the satellite-derived water levels. We find the residuals between the satellite data points and the reference line to be spatially clustered. A new method of evaluating model performance is developed to test the impact of this spatial dependency on model calibration. This method uses multiple random subsamples of the water surface elevation points that have no significant spatial dependency; tested for using Moran’s I. LISFLOOD-FP is then calibrated using conventional binary pattern matching and water elevation comparison both with and without spatial dependency. It is shown that model calibration carried out using pattern matching is negatively influenced by spatial dependency in the data. By contrast, calibration using water elevations produces realistic calibrated optimum friction parameters even when spatial dependency is present. Accounting for spatial dependency reduces the estimated modelled error and gives an identical result to calibration using spatially dependent data; it also has the advantage of being a statistically robust assessment of model performance in which we can have more confidence. Further, by using the variations found in the subsamples of the observed data it is possible to assess how the noisiness in these data affects our understanding of flood risk. This has highlighted the requirement for a probabilistic treatment of observed data, and using multiple subsamples is one way of achieving this.

Evaluating ScanSAR Interferometry Deformation Time Series Using Bursted Stripmap Data

We demonstrate scanning synthetic aperture radar (ScanSAR) advanced radar interferometry processing for surface deformation time series analysis. We apply the small baseline subsets (SBAS) technique to ScanSAR data synthesized from 40 ERS-1 and ERS-2 stripmap SAR images over known deformation in Phoenix, Arizona. The strategy is to construct a burst pattern similar to Envisat ScanSAR data for two scenarios, namely, an idealized 100% burst overlap case and a realistic variable-burst synchronization case in which any image pair has at least 50% burst overlap. We And this latter scenario to be reasonable based on an assessment of the effect of burst overlap on Phoenix interferometric phase coherence. The differences between the variable burst overlap ScanSAR and stripmap SAR SBAS-derived pixel velocities have a mean of 0.02 cm/year and a standard deviation of 0.02 cm/year. It is noted that one can expect SBAS velocity and displacement one-sigma errors of 0.1 cm/year and 0.5 cm, respectively, from multilooked stripmap data. We observe that 96% and 99% of the variable burst overlap ScanSAR pixel velocities are within ±0.1 and ±0.2 cm/year (one- and two-sigma), respectively, of our stripmap SAR pixel velocities. These results are similar to those reported for SBAS analysis applied to low-resolution multilook interferograms derived from coherence-preserving down sampling of stripmap data. We also And that the rms deviations between variable burst overlap ScanSAR and stripmap SBAS displacement estimates are 0.40 ± 0.30 cm. 68% and 94% of the variable burst overlap ScanSAR pixel displacements are within ±0.5 and ±1.0 cm, respectively, of the stripmap displacements.

GRAY TONE FILTERING ON ERS-SAR IMAGES APPLIED TO CHANGE DETECTION AND MAPPING

In SAR images, the pixel values are tightly related to physical parameters of the soil such as topography, roughness and humidity, regardless to atmospheric conditions. Therefore, SAR images may be used to detect, and quantify changes in land cover, by comparison of time series SAR data. Classical change detection techniques from SAR images are based on additive synthesis of RGB colors and arithmetic operations between images. The noisy aspect of ERS image due to the original speckle is an obstacle for available mapping and quantification of the changes. Here, statistical and morphological filters are used to reduce the speckle noise. Combined techniques of change detection and noise filtering are applied here to assess and map from ERS-SAR images the impact of regular or catastrophic flood and deforestation in the East Coast of Madagascar.

THE APPLICATION OF WAVELET ANALYSIS FOR INTERNAL WAVE DETECTION IN SAR AND OPTICAL IMAGES DATA OVER TSUSHIMA STRAIT

On this paper, wavelet analysis has been used for internal wave detection in ERS SAR and ASTER images data over Tsushima strait, southwest of Japan, during 1993-2004 period. Various wavelet transforms, such as Haar wavelet, Symlet wavelet, Coif wavelet, Daubechies wavelet, and Discreet Meyer wavelet, are tested comparably with different level of synthesize image on horizontal, diagonal, and vertical detail, and approximation to study the internal wave characteristic in image. Internal wave features were detected as elongated pattern in image with higher wavelet coefficient (>36) than sea surface (litlle than 10) on horizontal and vertical detail coefficient of image transforms at level 2-5. The decomposition image shows the tendency that the decomposition of internal wave feature using wavelet transform tends to follow the wavelet function. This may reduced the height of leading wave. Smoother result of internal wave shape can be formed using higher scale resolution of image and higher number of vanishing moments such as Daubechies waveletdb5, Symlet wavelet-sym5, and Discrete Meyer wavelet. The compactly supported wavelet function with orthogonal basis with scale function and FIR filter, such as discrete Meyer function is proposed for smoothness of feature, space save coding, and to avoid depashing in image. So far, the detection processes were performed well on the internal waves data that occurred at north coast off Kitakyushu and NW/W/SW/E coast off Tsushima Island on June to September period whose lengths were detected between 6-28 km and wavelength between 120m-1.28km. The directions of internal wave propagation were varied between NW-SW at eastern channel and N-SW at western channel of Tsushima Strait. Keywords: wavelet analysis, SAR image, optical image, internal wave.

Monitoring of Surface Deformation in Northern Taiwan Using DInSAR and PSInSAR Techniques

We investigated the surface deformation of the northern Taiwan area, including the Taipei basin and its surrounding mountainous areas of the last fifteen years using the ERS-1, ERS-2 and ENVISAT SAR images. Although the Taipei basin now is well developed and amenable to research gathering using the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique, the mountainous areas surrounding the basin are densely covered with various vegetation throughout different seasons inducing high noise ratio in interferograms. Therefore the DInSAR technique is ineffective for observation of surface deformations of these areas. As a result, we developed the Persistent Scatterer (PS) InSAR technique to extract the phase signal of the chosen PS points for this study. Our analysis result shows that the atmospheric disturbance and DEM residual can be successfully reduced and the precise information of surface deformation can be effectively obtained by the PSInSAR technique not only in the basin but also in the mountainous areas. Integrating the DInSAR and PSInSAR results, we observed conspicuous deformation events in northern Taiwan including: (1) the slight uplift in the Western Foothills, the Tatun volcanoes, the Linkou Tableland and the Taoyuan area; (2) the subsidence at the border of the Taipei basin; and (3) relative slight uplift rebound in the center of Taipei basin. The displacements along the Shanchiao, Chinshan, and Kanchiao Faults are large enough to be observed; the Taipei, Hsinchuang, and Nankang Faults are too small and cannot be discerned. Further comparison between the DInSAR, PSInSAR, and their corresponding leveling data shows a very coincidental pattern and measurably improves the authenticity of radar interferometry.

Evolution of post-seismic ground deformation of the Athens 1999 earthquake observed by SAR interferometry

Co-seismic interferometric analysis was performed to investigate the spatial and temporal evolution of ground deformation related to the aftershock sequence of the Athens 1999 earthquake ( M w = 6.0). Differential interferograms (DInSAR) spanning different periods after the main seismic event showed variable ground deformation associated with the evolution of the post-seismic displacement field. Using ERS SAR images, four co-seismic differential interferograms were generated for the period from September to December of 1999, and spanning 16, 32, 67 and 102 days after the occurrence of the main shock. It was found that the cumulative ground deformation detected by DInSAR analysis was exponentially decreasing, following the declining rate of the post-seismic activity. The observed propagation of the ground deformation maxima towards the SE direction is consistent with the presence of clustered aftershock activity to the east of the epicentral area. The aforementioned evolution of deformation was also recognized by the observed expansion of the displacement field to the east.

Use of multitemporal SAR data for monitoring vegetation recovery of Mediterranean burned areas

Remote sensing in the optical band is a well-established tool for monitoring changes in forested areas, although it can suffer from limitations, especially where frequent cloud cover occurs. The increased availability of space-borne radar imagery offers additional means for assessing the state of forests and monitoring their dynamics. In this study, the potential of multi-temporal space-borne SAR data for monitoring vegetation recovery over burned areas next to the Mediterranean coast is investigated. In particular, the study considers a set of ERS-SAR images, C-band and VV polarization, taken over the Castel Fusano pinewood, located near Rome, Italy, devastated in summer 2000 by a fire that burned about 350 ha of the wood. Starting from the analysis of the information contained in the variations, both in burnt and unburnt areas, of the inter annual multitemporal backscattering signatures, the study presents two different approaches, one more qualitative, the other one more quantitative, for the retrieval of the biomass re-growth after the fire. In the quantitative case, the inversion procedure computes the biomass re-growth rate by means of simulations carried out with the Tor Vergata scattering model. The obtained results are satisfactory as they are in agreement with simultaneous analysis based on optical data and in-situ measurement campaigns.

Two-dimensional Co-Seismic Surface Displacements Field of the Chi-Chi Earthquake Inferred from SAR Image Matching.

The Mw=7.6 Chi-Chi earthquake in Taiwan occurred in 1999 over the Chelungpu fault and caused a great surface rupture and severe damage. Differential Synthetic Aperture Radar Interferometry (DInSAR) has been applied previously to study the co-seismic ground displacements. There have however been significant limitations in the studies. First, only one-dimensional displacements along the Line-of-Sight (LOS) direction have been measured. The large horizontal displacements along the Chelungpu fault are largely missing from the measurements as the fault is nearly perpendicular to the LOS direction. Second, due to severe signal decorrelation on the hangling wall of the fault, the displacements in that area are un-measurable by differential InSAR method. We estimate the co-seismic displacements in both the azimuth and range directions with the method of SAR amplitude image matching. GPS observations at the 10 GPS stations are used to correct for the orbital ramp in the amplitude matching and to create the two-dimensional (2D) co-seismic surface displacements field using the descending ERS-2 SAR image pair. The results show that the co-seismic displacements range from about -2.0 m to 0.7 m in the azimuth direction (with the positive direction pointing to the flight direction), with the footwall side of the fault moving mainly southwards and the hanging wall side northwards. The displacements in the LOS direction range from about -0.5 m to 1.0 m, with the largest displacement occuring in the northeastern part of the hanging wall (the positive direction points to the satellite from ground). Comparing the results from amplitude matching with those from DInSAR, we can see that while only a very small fraction of the LOS displacement has been recovered by the DInSAR mehtod, the azimuth displacements cannot be well detected with the DInSAR measurements as they are almost perpendicular to the LOS. Therefore, the amplitude matching method is obviously more advantageous than the DInSAR in studying the Chi-Chi earthquake. Another advantage of the method is that the displacement in the hanging wall of the fault that is un-measurable with DInSAR due to severe signal decorrelation can almost completely retrieved in this research. This makes the whole co-seismic displacements field clearly visible and the location of the rupture identifiable. Using displacements measured at 15 independent GPS stations for validation, we found that the RMS values of the differences between the two types of results were 6.9 cm and 5.7 cm respectively in the azimuth and the range directions.

A region-based GLRT detection of oil spills in SAR images

In the study, we propose a fast region-based method for the detection of oil spills in SAR images. The proposed method combines the image segmentation technique and conventional detection theory to improve the accuracy of oil spills detection. From the image statistical characteristics, we first segment the image into regions by using moment preserving method. Then, to get a more integrated segmentation result, we adopt N-nearest-neighbor rule to merge the image regions according to their spatial correlation. Performing the split and merge procedure, we can partition the image into oil-polluted and sea reflection regions, respectively. Based on the segmentation results, we build data models of oil spills and approximate them by using normal distributions. Employing the built oil spills model and the generalized likelihood ratio test (GLRT) detection theory, we derive a closed form solution for oil spills detection. Our proposed method possesses a smaller variance and can reduce the confusion interval in decision. Moreover, we adopt the sample average of image region to reduce the computation complexity. The false alarm rate and oil spills detection probability of the proposed method are derived theoretically. Under the criterion of constant false alarm ratio (CFAR), we determine the threshold of the decision rule automatically. Simulation results performed on ERS2-SAR images have demonstrated the efficiency of the proposed approach.

Automatic detection of main road network in dense urban area using microwave SAR images

A hybrid method of edge detection of radar images and classification of fused infrared and microwave SAR images is developed for automatic detection of the main road network in a dense urban area. Fusion of the infrared and microwave SAR images effectively reduces the noise in the edge detection and also effectively removes possible confusion with non-road objects, i.e. linearly featured rivers in the classification. Possible road candidates are further processed using the morphological thinning algorithm. Road linking and extension are carried out hierarchically according to the characteristics of the main roads as well as their connections. Finally, the main road network is successfully established from the SAR image. The approach is effective and accurate in detecting road segments and linking without complicated mathematic models, e.g. the Snake or Genetic Algorithms. As an example, using the ERS-2 SAR image data, automatic detection of the main road network in Shanghai Pudong area is presented.

Active deformation of Tainan tableland of southwestern Taiwan based on geodetic measurements and SAR interferometry

The D-InSAR technique is applied to detect the active fault-related folding structure of the Tainan tableland near the deformation front in SW Taiwan by using ERS SAR images during 1996–2000. The Tainan tableland is located in-between a blind fault in the west and the Houchiali fault in the east, thus the Tainan tableland is interpreted as a pop-up structure in a fold-thrust belt at active tectonic margin. Interferometric processing of six SAR images reveals the average slant range deformation (SRD) as ~ 12.5 mm/yr. The uplift rate is higher in eastern Tainan tableland than that in western Tainan tableland, and it increases from west edge of Tainan tableland and decreases across the Houchiali fault. The campaign-mode GPS data set from 1999 to 2003 indicate an average horizontal movement of 12 ± 4 mm/yr in the direction of N44°W for the Tainan tableland with respect to western coastline. Furthermore 5 precise leveling surveys across Tainan tableland over a period of 2 years show an uplift rate of ~ 14 mm/yr for the benchmarks on the tableland. Based on the 2-D analytical solution with the constraint of he inferred fault geometry, the slip rate along the inferred Tainan fault is ~ 16 mm/yr, ~ 10 mm/yr along the Houchiali fault, and ~ 25 mm/yr along the inferred Chungchou fault. Consequently we propose that active deformation of the Tainan tableland is likely resulted from the freely slipping of the Tainan fault and the Houchiali fault. The locking depth should be located on the deeper part of décollement, eastern of the Chungchou fault. In addition, the combination of D-InSAR, GPS data and the precise leveling data reveals that the short-term deformation rate is larger than long-term deformation rate, which implies that a destructive seismic event could occur in the eastern Tainan area.

Statistical modelling of multimodal SAR images

This paper discusses the statistical modelling of multimodal SAR image histograms. We use a generalized mixture of distributions with flexible shapes that are likely to fit the SAR image histogram. We then form a system called GGBL, composed of four parametric distributions (Gaussian, Gamma, Beta and Log‐Normal). Selection of a parametric distribution from the GGBL system for each mode of the multimodal SAR histogram is performed according to the location of the skewness and flatness coefficients in this space. We propose a distribution stability method for distribution selection, using the asymmetry and flatness coefficients, and a feature method for the estimation of the parameters of these distributions based on the characteristic points of the histogram. The GGBL system is applied to real histograms of RADARSAT and ERS SAR images with different numbers of looks. The results obtained are promising.