scholarly journals A NEW STRATEGY FOR PHASE UNWRAPPING IN INSAR TIME SERIES OVER AREAS WITH HIGH DEFORMATION RATE: CASE STUDY ON THE SOUTHERN TEHRAN SUBSIDENCE

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 35-40 ◽  
Author(s):  
P. Ajourlou ◽  
S. Samiei Esfahany ◽  
A. Safari
Keyword(s):  
Deformation Gradient ◽  
Small Deformation ◽  
Phase Unwrapping ◽  
Bayesian Estimator ◽  
High Deformation ◽  
New Strategy ◽  
Small Baseline Subset ◽  
Spatio Temporal ◽  
Small Baseline

Abstract. The primary step in all timeseries interferometric synthetic aperture radar (T-InSAR) algorithms is the phase unwrapping step to resolve the inherent cycle ambiguities of interferometric phases. In areas with a high spatio-temporal deformation gradient, phase unwrapping fails due to the aliasing problem, and so it can result in an underestimation of deformation signal. One way to handle this problem is to use the so called Small-Baseline Subset (SBAS) algorithms; in these algorithms, by using only small-baseline interferograms – hence interferograms with small deformation gradients – the chance of unwrapping error gets reduced. However, due to more number of the used interferograms, SBAS method is computationally more expensive and more time-consuming compared to algorithms that exploit Single-Master (SM) stacks. Moreover, the existence of sufficiently small temporal baseline interferograms is not guaranteed in all SAR stacks. In this paper, we propose a new method to take advantage of short temporal baseline interferograms but effectively using SM approach. We treat the phase unwrapping step as a Bayesian estimation problem while the prior information, required by the Bayesian estimator, is extracted from few short coherent interferograms that are unwrapped separately. Results from the proposed approach and a case study over the southwest of Tehran, with a high subsidence rate (reaching to 25 cm/year), demonstrates that utilizing the proposed method overcomes the aliasing problem and produces the results equal to the conventional SBAS results, while the proposed method is computationally much more efficient than SBAS.

scholarly journals TWO-DIMENSIONAL LOESS LANDSLIDE DEFORMATION MONITORING WITH MULTIDIMENSIONAL SMALL BASELINE SUBSET (MSBAS) – A CASE STUDY OF XINYUAN No.2 LANDSLIDE, GANSU, CHINA

2018 ◽  
Vol XLII-3 ◽  
pp. 2341-2345
Author(s):  
C. Y. Zhao ◽  
X. J. Liu ◽  
W. Zhu ◽  
W. F. Zhu
Keyword(s):  
Deformation Monitoring ◽  
Vertical Deformation ◽  
Two Dimensional ◽  
Loess Landslide ◽  
Landslide Deformation ◽  
Small Baseline Subset ◽  
Small Baseline ◽  
First Time ◽  
East West

The deformation monitoring of active landslides is of great importance for the safety of human lives and properties. And twodimensional deformation result can give us more thoughts on the landslide type and deformation process. In this study, multidimensional small baseline subsets (MSBAS) technique is introduced and tested to compute two-dimensional deformation rate and time series for both east-west and vertical deformation of Xinyuan No.2 landslide by simultaneously processing ascending and descending TerraSAR-X data acquired from January 2016 to November 2016. Results show not only the spatiotemporal characteristics of this landslides, but the retrogressive loess landslide failure mode is revealed for the first time with the two-dimensional deformation.

scholarly journals One-Step Three-Dimensional Phase Unwrapping Approach Based on Small Baseline Subset Interferograms

2020 ◽  
Vol 12 (9) ◽  
pp. 1473 ◽  
Author(s):  
Christina Esch ◽  
Joël Köhler ◽  
Karlheinz Gutjahr ◽  
Wolf-Dieter Schuh
Keyword(s):  
Spatial Information ◽  
Real Data ◽  
Single Step ◽  
Phase Unwrapping ◽  
Motion Model ◽  
Phase Gradient ◽  
Spatial Phase ◽  
Small Baseline Subset ◽  
Temporal And Spatial ◽  
Small Baseline

One of the most critical steps in a multitemporal D-InSAR analysis is the resolution of the phase ambiguities in the context of phase unwrapping. The Extended Minimum Cost Flow approach is one of the potential phase unwrapping algorithms used in the Small Baseline Subset analysis. In a first step, each phase gradient is unwrapped in time using a linear motion model and, in a second step, the spatial phase unwrapping is individually performed for each interferogram. Exploiting the temporal and spatial information is a proven method, but the two-step procedure is not optimal. In this paper, a method is presented which solves both the temporal and spatial phase unwrapping in one single step. This requires some modifications regarding the estimation of the motion model and the choice of the weights. Furthermore, the problem of temporal inconsistency of the data, which occurs with spatially filtered interferograms, must be considered. For this purpose, so called slack variables are inserted. To verify the method, both simulated and real data are used. The test region is the Lower-Rhine-Embayment in the southwest of North Rhine-Westphalia, a very rural region with noisy data. The studies show that the new approach leads to more consistent results, so that the deformation time series of the analyzed pixels can be improved.

scholarly journals Method Combining Probability Integration Model and a Small Baseline Subset for Time Series Monitoring of Mining Subsidence

2018 ◽  
Vol 10 (9) ◽  
pp. 1444 ◽  
Author(s):  
Hongdong Fan ◽  
Lu Lu ◽  
Yahui Yao
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Deformation Gradient ◽  
Mining Area ◽  
Mining Subsidence ◽  
Interferometric Synthetic Aperture Radar ◽  
Integration Model ◽  
Small Baseline Subset ◽  
Maximum Subsidence ◽  
Small Baseline

Time Series Interferometric Synthetic Aperture Radar (TS-InSAR) has high accuracy for monitoring slow surface subsidence. However, in the case of a large-scale mining subsidence areas, the monitoring capabilities of TS-InSAR are poor, owing to temporal and spatial decorrelation. To monitor mining subsidence effectively, a method known as Probability Integration Model Small Baseline Set (PIM-SBAS) was applied. In this method, mining subsidence with a large deformation gradient was simulated by a PIM. After simulated deformation was transformed into a wrapped phase, the residual wrapped phase was obtained by subtracting the simulated wrapped phase from the actual wrapped phase. SBAS was used to calculate the residual subsidence. Finally, the mining subsidence was determined by adding the simulated deformation to the residual subsidence. The time series subsidence of the Nantun mining area was derived from 10 TerraSAR-X (TSX) images for the period 25 December 2011 to 2 April 2012. The Zouji highway above the 9308 workface was the target for study. The calculated maximum mining subsidence was 860 mm. The maximum subsidence for the Zouji highway was about 145 mm. Compared with the SBAS method, PIM-SBAS alleviates the difficulty of phase unwrapping, and may be used to monitor large-scale mining subsidence.

Monitoring land subsidence and fault deformation using the small baseline subset InSAR technique: A case study in the Datong Basin, China

2014 ◽  
Vol 75 ◽  
pp. 34-40 ◽  
Author(s):  
Cheng-sheng Yang ◽  
Qin Zhang ◽  
Chao-ying Zhao ◽  
Qing-liang Wang ◽  
Ling-yun Ji
Keyword(s):  
Land Subsidence ◽  
Datong Basin ◽  
Small Baseline Subset ◽  
Fault Deformation ◽  
Small Baseline

scholarly journals Feasibility of Artificial Slope Hazards Identification in Regional Mountainous Highway Using SBAS-InSAR Technique: A Case Study in Lishui, Zhejiang

2021 ◽  
Vol 11 (19) ◽  
pp. 8962
Author(s):  
Zhi Hu ◽  
Danqiang Xiao ◽  
Wei Zhan ◽  
Yang Yu ◽  
Yiqiang Yu ◽  
...  
Keyword(s):  
Ground Deformation ◽  
Low Cost ◽  
Hazard Identification ◽  
Interferometric Synthetic Aperture Radar ◽  
Large Area ◽  
Small Baseline Subset ◽  
Small Baseline ◽  
Sbas Insar ◽  
Safe Condition

Safety status of artificial slopes is significant for the operation and maintenance of highway to mitigate the risk; thus, slope hazard identification is necessary. In order to realize large-area and low-cost application for regional highway, taking the Longqing Highway (length of 55 km) as a case study, the SBAS-InSAR (Small Baseline Subset-Interferometric Synthetic Aperture Radar) technique is adopted to detect the ground deformation and conduct hazard identification based on slope dip, aspect, geological data and historical hazard record. Field survey is carried out to verify the identified potential hazards. Results show that the detected potential hazards are distributed mainly in the areas consisting of granite residual and the Quaternary soil. Six potential hazards identified by the SBAS-InSAR-based method are roughly in accordance with the on-site verification. It is suggested that the SBAS-InSAR technique has the ability to obtain the slope deformation accurately and reveal the safe condition of the slopes. The SBAS-InSAR technique can be suitable for assistance in regional highway slope inspection.

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