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Conference Agenda

Overview and details of the sessions and sub-session of this conference. Please select a date or session to show only sub-sessions at that day or location. Please select a single sub-session for detailed view (with abstracts and downloads if available).

 
Session Overview
Session
D2: ID.10665 Terrain Motion & Landslides Case Studies
Time:
Tuesday, 05/Jul/2016:
2:00pm - 3:00pm

Session Chair: Cécile Lasserre
Session Chair: Qiming Zeng
Workshop: Terrain & Geoid Measurement
Location: A-Li Mountain Room, 5.5 Floor, Junyi Dynasty Hotel

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Presentations
Oral presentation

Application of Spaceborne ScanSAR SBAS Analysis in the Deformation Monitoring of the West Section of Altyn Tagh Fault System

Lin Shen, Qiming Zeng, Jian Jiao

Institute of Remote Sensing and GIS, Peking University, Beijing, People's Republic of China;

The deformation monitoring of active faults is significant for studying the mechanism of earthquakes and can minimize the adverse effects on social development as well. Compared with the traditional differential Synthetic Aperture Radar Interferometry (D-InSAR) method, InSAR time series analysis is able to overcome the limitations of temporal and geometrical decorrelation, and to compensate error contributions from atmospheric distortions, inaccurate terrain model and satellite orbit errors as well. As one of important categories in InSAR time series analysis, small baseline subset (SBAS) algorithm estimates the deformation time series based on singular value decomposition. So far, SBAS analysis with stripmap SAR data has been widely applied to the deformation monitoring of active faults. However, as the dimension in range direction of stripmap SAR data is small, sometimes it is unable to cover the whole research area especially when studying large fault systems or faults striking from west to east. Consequently, in order to breakthrough the restriction of space, we present a SBAS processing chain utilizing Envisat ASAR ScanSAR data, of which the distance in range direction is around four times of that in the stripmap mode, and then applyit to monitor the deformation in the west section of Altyn Tagh Fault (ATF) system.

The proposed processing chain mainly includes (1) Analyzing ScanSAR raw data, calculating Doppler centroid frequency and focusing ScanSAR raw data with full aperture algorithm; (2) Calculating time baseline, perpendicular baseline and burst synchronization, and then selecting small baseline pairs; (3) ScanSAR subswath interferometry processing; (4) Mosaicking subswath interferograms by using overlap area smoothing method and (5) Estimating deformation time series of the whole merging area with New SBAS (NSBAS) algorithm. Finally, based on 27 Envisat ASAR ScanSAR raw data images, we acquire the geocoded accumulative displacement map of the west section of ATF in the radar line-of-sight direction from February 2007 to September 2010. According to the results, the average displacement rate of D-InSAR time series analysis is consistent with the measurements of GPS I070 station, demonstrating that our way of SBAS analysis with spaceborne ScanSAR data is effective for monitoring the deformation of active faults. Moreover, the experimental results also show that InSAR time series analysis with spaceborne ScanSAR data is able to derive the deformation signal of large area simultaneously without coverage dropping, thus avoiding the merging problem caused by the inconsistent measurements between adjacent tracks in InSAR time series analysis with stripmap SAR data.

Shen-Application of Spaceborne ScanSAR SBAS Analysis in the Deformation Monitoring of the West Section of_Cn_version.pdf

Oral presentation

Persistent Scatterer SAR Interferometry Time Series Analysis and Applications in Deformation Monitoring of Reservoirs

Ruya Xiao, Xiufeng He, Mi Jiang

Hohai University, China, People's Republic of;

Interferometric Synthetic Aperture Radar (InSAR) technology characterized by high monitoring precision, large scale and continuous spatial coverage, has been extensively used in deformation monitoring of seismological research and urban subsidence, etc. The current InSAR time series analysis methods have achieved outstanding performances in urban areas containing large numbers of man-made structures. However, they are not completely suitable for the natural environments in hydro project areas. To circumvent the difficulties of InSAR time series analysis in deformation monitoring of reservoirs, a systematic research of methodologies and applications is carried forward in this paper, considering the complexity and particularity of the application environment.

1. The sub-pixel fine registration of Synthetic Aperture Radar (SAR) images would be difficult due to the spatial and temporal decorrelation when applying InSAR time series analysis in the deformation monitoring of reservoirs. To solve this problem, a mathematic model of transfer registration through introducing the auxiliary image(s) is constructed based on the SAR images regular registration process. A corresponding experiment is designed, to compare the registration results from both regular and the transfer registration methods in different correlation conditions. Consistency, fringe quality of the interferogram and the distribution of correlation coefficients are proposed to qualitatively and quantitatively judge the accuracy of the registration results. Results show that the transfer registration is a more robust method and can achieve more accurate results, especially in the serious decorrelation conditions. The accuracy can have an increase of 58.9% and 65.8% in the range and azimuth directions, respectively, when compared with that of regular registration method.

2. Reservoirs are usually covered with a large area of water, and the study area consists of a variety of land cover types. Therefore, detection of Persistent Scatterer (PS) by using InSAR time series analysis may lead to erroneous interpretation. To solve this problem, based on the SAR amplitude image statistical natures, a PS selection method employing amplitude and stability analysis of interferometric phase with adaptive threshold segmentation result as the additional constraint is proposed. The experiment using ENVISAT ASAR data acquired over Guangnan Reservoir in Shandong Province, China, is carried out. Results show that the proposed method not only increases the spatial intensity of PS, but also reduces the “false positive” of PS, so as to improve the accuracy of InSAR time series displacement estimation. Hence, it is a suitable PS selection means for complicated application environment in reservoirs.

3. The surface displacement is influenced by various factors in reservoir areas, such as complex geological conditions, thus the deformation pattern cannot be always known in advance. Classical PSI (Persistent Scatterer Interferometry) requires a model for the deformation with time to estimate the deformation for each PS. Through integrating the spatial two-dimensional sparse grid phase unwrapping method and temporal one-dimensional phase unwrapping, a temporal-spatial unwrapping and deformation parameter estimation method without any prior assumptions about the displacement is proposed. The results from real data experiment carried out over the reservoir of Pubugou Hydropower Station in Southwest China show that there are periodic displacements in the study area. The proposed method can effectively extract non-linear displacement, hence expanding the InSAR time series deformation parameter estimation to non-linear deformation without prior knowledge of temporal variations in the deformation rate.

4. Two reservoirs in North China Plain, along the Eastern Route Project of South-to-North Water Diversion are selected as the study area to validate the InSAR time series analysis method proposed in the paper. The SAR images transfer registration method, PS selection method with adaptive threshold segmentation result as the additional constraint and temporal-spatial unwrapping and deformation parameter estimation method are employed to monitor the deformation of the two reservoirs temporally and spatially. Results reveal that the average deformation rates of the coastal water defense on Laizhou Bay and the eastern bank of Guangnan Reservior suffering from corrosion by seawater are 5 mm/year and 3 mm/year, respectively, and the western bank and the artificial promenade in the middle of the lake remain stable. High-quality PS can be detected and high-accuracy deformation time series can be extracted by the proposed method in this dissertation, which verifies that it is effective in spatial-temporal continuous deformation monitoring of reservoirs through InSAR time series analysis.

Xiao-Persistent Scatterer SAR Interferometry Time Series Analysis and Applications_Cn_version.pdf

Oral presentation

Remote Sensing of Deformation of a High Concrete-Faced Rockfill Dam Using InSAR: A Study of the Shuibuya Dam, China

Zhiwei Zhou, Wei Zhou, Shaolin Li, Xiaolin Chang

Wuhan University, China, People's Republic of;

Settlement is one of the most important deformation characteristics of high concrete faced rockfill dams (CFRDs, >100 m). High CFRDs safety would pose a great threat to the security of people’s lives and property downstream if this kind of deformation were not to be measured correctly, as traditional monitoring approaches have limitations in terms of durability, coverage, and efficiency. It has become urgent to develop new monitoring techniques to complement or replace traditional monitoring approaches for monitoring the safety and operation status of high CFRDs. This study examines the Shuibuya Dam (up to 233.5 m in height) in China, which is currently the highest CFRD in the world. We used space-borne Interferometric Synthetic Aperture Radar (InSAR) time series to monitor the surface deformation of the Shuibuya Dam. Twenty-one ALOS PALSAR images that span the period from 28 February 2007 to 11 March 2011 were used to map the spatial and temporal deformation of the dam. A high correlation of 0.93 between the InSAR and the in-situ monitoring results confirmed the reliability of the InSAR method; the deformation history derived from InSAR is also consistent with the in-situ settlement monitoring system. In addition, the InSAR results allow continuous investigation of dam deformation over a wide area that includes the entire dam surface as well as the surrounding area, offering a clear picture continuously of the dam deformation.

Zhou-Remote Sensing of Deformation of a High Concrete-Faced Rockfill Dam Using InSAR_Cn_version.pdf

Poster

Comparison of Two Persistent Scatter Interferometry Algorithms in Deformation Monitoring of Altyn Area

Junsong Huang, Qiming Zeng, Jian Jiao

Institute of Remote Sensing and GIS, Peking University, Beijing, People's Republic of China;

1. Introduction

As is known to all, Altyn Tagh Fault has always been a hot research area because of a high incidence of earthquake. The study of contemporary crustal velocity field along the fault is important for seismic study. Nowadays, as an innovative time series analysis technique, Persistent Scatter (PS) Synthetic Aperture Radar (SAR) Interferometry (PSInSAR) has been widely and successfully used in various ground deformation monitoring applications, including landslide monitoring, subsidence in cities and mining area, seismic studies, etc. This technique focuses on PS which shows point-like stable scattering characteristics in long-time span data stacks, and is supposed to overcome conventional InSAR’s limitation in critical spatial-temporal baseline and to reconstruct the long-time deformation history of PS. Now, there are several algorithms developed in PSInSAR, including Interferometric Point Target Analysis (IPTA) implemented in GAMMA software, Stanford Method for Persistent Scatters (StaMPS) implemented in StaMPS software, and an algorithm implemented in Delft PS Interferometric processing package (DePSI), etc. In this paper, we focus only on GAMMA IPTA and StaMPS, other algorithm’s research, application and comparison will be future work.

GAMMA IPTA and StaMPS are two widely used software, and have been successfully applied in various ground deformation phenomenon studies. GAMMA IPTA sets a pre-defined linear deformation model for the study area, while StaMPS are designed without any assumption about ground deformation temporal evolution. Furthermore, IPTA selected PS based on their amplitude variation in time, while StaMPS based on the correlation of their phase in space. In all, they have differences in deformation model assumption, PS selection method, phase unwrapping and differential phase modeling. Because of their different characteristic, researchers will facing the question that which has better performance on their own specific research area.

Focusing on the comparison of the two different algorithms, IPTA and StaMPS. We want to explore their potential and performance in monitoring of surface deformation, mainly including PS density, distribution, coherence and accuracy of deformation results which is verified by GPS measurements. GPS measurements provide ideal reference data to evaluate the accuracy of reconstructed displacement history with different PS algorithms.

2. Study Area and Datasets

The research area is located in the north of Altyn Tagh Fault, and total area is about 90km (range)×40km (azimuth). The upper left coordinates is (37.26°N, 82.13°E) and the lower right is (36.70°N, 83.33°E ). The left half of research area covers wind erosion landforms, the right half covers pluvial fan and the top center covers part of Minfeng country where contains many buildings and covers a certain degree of vegetation. The elevation decreases from south-east to north-west. In this study, 24 ENVISAT ASAR images (IM mode, descending, VV polarization) were acquired, covering the period from 2006 Oct. to 2010 Aug. One GPS station was located in the area whose corresponding LOS velocity is about -2.33mm/y, measuring time from 1999 to 2011.

3. Experimental Results

As for PS density, they were almost the same, 1016.7 per kilometer for StaMPS and 944.89 per kilometer for IPTA. But, the distribution of PS selected by StaMPS was more uniform than that by IPTA, e.g. StaMPS can not only selected lots of PS in high coherence area such as pluvial fan and built-up areas, but also selected enough PS in the relative low coherence areas such as wind erosion landforms, while almost all the selected PS in GAMMA IPTA was in the pluvial fan and a small number was distributed in built-up area.

As for the uniformity of ground deformation velocity, StaMPS was better. Furthermore, the results in GAMMA seemed to show obvious difference between both sides of the ridgeline, the left side of ridgeline is much stable, velocity from -1mm/y to 1mm/y, and right side is being towards SAR, velocity from 1mm/y to 4mm/y. While the StaMPS result shows stable deformation on both sides of ridgeline, velocity from -0.4mm/y to 1mm/y.

When compared with GPS measurements, both of them have some differences. For StaMPS, there are 4 PS within 300 meters of GPS. Their average velocity is about -1.25mm/y. For GAMMA IPTA, one PS was found within 1000 meters of GPS and its velocity is about 0.397mm/y. Besides, PS in GAMMA shows a linear deformation, while PS in StaMPS do not. As a whole, they have different type of velocity estimation in the overlap area, in some area the results are almost the same, in another area are not.

4. Conclusions

Based on analysis on the PS density and distribution, the quality and accuracy of results from the two PS modules, the conclusions regarding the strengths and limitations of the compared PS algorithm are as follows: 1) they are overall capable of providing a ground deformation time series analysis, especially in high coherence region. 2) StaMPS may be better in the estimation of deformation monitoring for this non-urban area, the reason may has a relationship with its PS selection method which results in a more uniform PS distribution. 3) StaMPS may be better than IPTA for big research area processing. For example, the area in this paper is 90km (range)×40km (azimuth), PS candidates far from reference PS will be removed with a large possibility because of the big differential in atmospheric phase when doing regression analysis in GAMMA IPTA. 4) GAMMA IPTA sets a linear assumption for the ground deformation, while StaMPS doesn’t. So, without prior knowledge about the research area, choosing StaMAP is reasonable. In all, various factors need to be considered when choosing PS algorithm, including prior knowledge on deformation, spatial scale of deformation field, ground cover, etc.

Huang-Comparison of Two Persistent Scatter Interferometry Algorithms_Cn_version.pdf

Poster

Assessment of the potential of TerraSAR-X Staring Spotlight data for monitoring ground deformation in densely vegetated terrain in the Three Gorges Region of China

Luyi Sun, Jan-Peter Muller

University College London, United Kingdom;

Conventional differential Interferometric Synthetic Aperture Radar (dInSAR) techniques are routinely used in accurate deformation mapping including landslide activities. However, several difficulties arise when attempting to use dInSAR in areas with steep topography, high humidity and dense vegetation cover such as the Three Gorges Region. In the case of very fast slope movements, due to the limitations of dInSAR with regard to the maximum detectable displacement (MMD), dInSAR techniques are not able to correctly measure these high landslide rates.

As an alternative method, sub-Pixel Offset Tracking (sPOT) method has recently been employed to derive centimetre-level land movement from artificial Corner Reflectors (CRs). A further statistical analysis was carried out on the deformation measurements derived from artificial Corner Reflectors versus natural scatterrers in densely vegetated terrain. The results indicate that even sPOT measurements in areas suffering from lower dInSAR coherence, are still able to correctly measure ground deformation range in densely vegetated terrain.

With the availability of super high resolution TerraSAR-X Staring Spotlight (TSX-ST) data, the ground deformation monitoring of Shuping landslide site in the Three Gorges Region is continued using the offset tracking techniques to achieve a higher accuracy. In addition, the potential of TSX-ST data of measuring surface deformation using dInSAR techniques is re-assessed in this area as well as a new field site, in particular whether the improvement of the resolution of Staring Spotlight mode helps to address some of the issues that were encountered previously.

The potential and limitations of sPOT and dInSAR techniques are compared on landslide monitoring using TSX Staring Spotlight data over Shuping landslide area.

This work is partially supported by the CSC and UCL through a PhD studentship at UCL-MSSL.

Sun-Assessment of the potential of TerraSAR-X Staring Spotlight data_Cn_version.pdf

Poster

A Comparison of Processing of Atmospheric Correction in Repeat-pass Spaceborne InSAR Measurement

Xinyi Wang, Qiming Zeng, Jian Jiao

Peking University, China, People's Republic of China;

A major source of errors for repeat-pass spaceborne Interferometric Synthetic Aperture Radar(InSAR) is the phase delay in radar signal propagation. Removing the phase delay especially the atmospheric phase delay is always very important in the conventional InSAR processing.

As for removal of atmospheric phase delay, the processing of atmospheric correction of common software such as GAMMA, GIAnT, StaMPS is applying atmospheric correction before the estimation of residual orbit errors. However, the reason why almost all common software apply atmospheric correction before the estimation of residual orbit errors almost haven`t been studied yet. There are almost not studies about comparing the result of applying atmospheric correction ahead and that of applying atmospheric correction after estimation of residual orbit errors to prove the accuracy of the common processing of atmospheric correction. It is worth exploring whether applying atmospheric correction ahead may get a more accuracy result than later.

Whether this atmospheric correction processing is reasonable in theory will be discussed in this paper. Actually, it is commonly known that the spatial distribution characteristics of atmosphere phase include turbulence structure and the vertical stratification which is relevant to the topography, While residual orbit errors also are relevant to topography. If applying estimation of residual orbit errors ahead, water vapor effects could cover the residual orbital fringes or both of them may be mixed together. Atmospheric correction applied later even may lead to negative topography. And then some comparative experiments utilizing the SAR image of Bam earthquake about atmospheric correction ahead and later will be done to attempt to demonstrate that applying atmospheric correction ahead instead of applying the estimation of residual orbit errors before atmospheric corrections may get a more accuracy result.

Wang-A Comparison of Processing of Atmospheric Correction_Cn_version.pdf

Poster

Automatic Extraction with Surface Elevation Calibration of Polar Icecap Layers on the Earth and Mars

Siting Xiong, Jan-Peter Muller

University College London, United Kingdom;

Ice penetrating radar is operating at low frequency of several to hundreds megahertz and has been applied into the field of subsurface investigation on both the Earth and Mars. On the Earth polar regions, i.e. Antarctica and Greenland, the Multichannel Coherent Radar Depth Sounder (MCoRDS) onboard IceBridge missions[1] since 2009 has collected radar profiles, which show the subsurface ice layers including isochronous layers caused by ice accumulation and disrupted layers caused by ice folding or ice flow.

On the other hand, in Martian polar regions, subsurface layers are also detected by low frequency radar systems, i.e. MARSIS (Mars Advanced Radar for Subsurface Ionosphere Sounding on board ESA’s Mars Express) and SHARAD (SHAllow subsurface RADar on board NASA’s Mars Reconnaissance Orbiter) [2]–[5]. Although the layers are formed due to different mechanisms from those in the Earth polar regions, the detection of subsurface layers are very important preliminary work in order to correlate them to further studies, such as surface evolution and past climate on Mars.

This study will present a method based on Radon Transform (RT) to automatic extract the subsurface layers with calibration of surface and bottom elevation by surface DTMs, such as DEM from the GIMP (the Greenland Ice Mapping Project) on the Earth polar region and HRSC, CTX, MOLA and HiRISE DTMs on Mars, and bedrock elevations respectively.

References

[1] J. Li, J. Paden, C. Leuschen, F. Rodriguez-Morales, R. D. Hale, E. J. Arnold, R. Crowe, D. Gomez-Garcia, and P. Gogineni, “High-Altitude Radar Measurements of Ice Thickness Over the Antarctic and Greenland Ice Sheets as a Part of Operation IceBridge,” Geosci. Remote Sensing, IEEE Trans., vol. 51, no. 2, pp. 742–754, Feb. 2013.

[2] R. Jordan, G. Picardi, J. Plaut, K. Wheeler, D. Kirchner, A. Safaeinili, W. Johnson, R. Seu, D. Calabrese, E. Zampolini, A. Cicchetti, R. Huff, D. Gurnett, A. Ivanov, W. Kofman, R. Orosei, T. Thompson, P. Edenhofer, and O. Bombaci, “The Mars express MARSIS sounder instrument,” Planet. Space Sci., vol. 57, no. 14{â}15, pp. 1975–1986, 2009.

[3] R. Orosei, R. L. Jordan, D. D. Morgan, M. Cartacci, A. Cicchetti, F. Duru, D. A. Gurnett, E. Heggy, D. L. Kirchner, R. Noschese, W. Kofman, A. Masdea, J. J. Plaut, R. Seu, T. R. Watters, and G. Picardi, “Mars Advanced Radar for Subsurface and Ionospheric Sounding (MARSIS) after nine years of operation: A summary,” Planet. Space Sci., vol. 112, pp. 98–114, 2015.

[4] F. Fois, R. Mecozzi, M. Iorio, D. Calabrese, O. Bombaci, C. Catallo, A. Croce, R. Croci, M. Guelfi, E. Zampolini, D. Ravasi, M. Molteni, P. Ruggeri, A. Ranieri, and M. Ottavianelli, “Comparison between MARSIS & SHARAD Results,” pp. 2134–2139, 2007.

[5] L. Castaldo, A. Séjourné, and R. Orosei, “SHARAD detection model of buried CO2 ice in Mars South Polar Layered Deposit,” in 3rd Planetary Cryosphere Workshop, 2015.

Xiong-Automatic Extraction with Surface Elevation Calibration_Cn_version.pdf
Xiong-Automatic Extraction with Surface Elevation Calibration_ppt_present.pdf


 
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