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 Using Multisensor SAR Datasets to Monitor Land Subsidence in Los Angeles from 2003 to 2017

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Bo Hu ◽  
Xiongle Chen ◽  
Xingfu Zhang
Keyword(s):  
Los Angeles ◽  
Land Subsidence ◽  
Disaster Prevention ◽  
Practical Application ◽  
Gps Measurements ◽  
The Past ◽  
Groundwater Overexploitation ◽  
Small Baseline Subset ◽  
Temporal And Spatial ◽  
Small Baseline

Los Angeles has undergone tremendous deformations over the past few decades, mainly due to human factors such as natural disasters and earthquakes, urban construction, overexploitation of groundwater, and oil extraction. The purpose of this study is to map the temporal and spatial variations of land subsidence in Los Angeles and to use the improved SBAS (small baseline subset) technique and multisensor SAR datasets to analyze the causes of deformations in this area from October 2003 to October 2017. At the same time, the deformation results of SBAS inversion are compared with the GPS measurements and the multisensor SAR dataset deformation, and the results are highly consistent. During the period from 2003 to 2017, there were several subsidence regions and one uplift region in Los Angeles. The cumulative subsidence was -266.8 mm at the maximum, and the average annual subsidence velocity was -19 mm/yr, which was mainly caused by groundwater overexploitation. The maximum amount of accumulated lift is +104.8 mm, and the average annual lifting velocity can reach +7.5 mm/yr. Our results have very strong practical application value and can provide a significant basis for local government services in disaster prevention and mitigation decision-making.

scholarly journals On the Analysis of the Phase Unwrapping Process in a D-InSAR Stack with Special Focus on the Estimation of a Motion Model

2019 ◽  
Vol 11 (19) ◽  
pp. 2295 ◽  
Author(s):  
Christina Esch ◽  
Joël Köhler ◽  
Karlheinz Gutjahr ◽  
Wolf-Dieter Schuh
Keyword(s):  
Minimum Cost ◽  
Large Data ◽  
Real Data ◽  
Search Space ◽  
Good Alternative ◽  
Phase Unwrapping ◽  
Phase Coherence ◽  
Model Parameters ◽  
Special Focus ◽  
Motion Model

This paper analyses the critical phase unwrapping step in a differential interferometric phase (D-InSAR) stack where both the solving of conventional methods and alternative approaches are discussed. It can be shown that including the temporal relationship between interferograms in the phase unwrapping step improves the results. This leads to the three-dimensional extended minimum cost flow algorithm. To unwrap the phase in a multitemporal way a motion model has to be considered. The estimation of these parameters is an important step. By default, the parameters are estimated in an iterative search process, where in each step, a linear program has to be solved. The best parameters are defined by the minimal costs. Often the choice of this search space is not straightforward. Furthermore, with this discrete optimization function, the solution is often not unique. This paper presents an alternative way to estimate the motion model parameters by maximizing a continuous function, the ensemble phase coherence. With the help of a closed-loop simulation and real data, both methods, the standard and the alternative way, are numerically compared and analyzed. Consequently, it is shown that maximizing the ensemble phase coherence is a good alternative to the established iterative procedure. It offers the advantage that the run time can be reduced considerably and is thus well suited in the processing of large data sets.

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.

Phase unwrapping based on the phase‐gradient‐jump connections

2017 ◽  
Vol 53 (10) ◽  
pp. 683-685 ◽  
Author(s):  
Tao Zhang ◽  
Xiaolei Lv ◽  
Jiang Qian ◽  
Jun Hong ◽  
Ye Yun
Keyword(s):  
Phase Unwrapping ◽  
Phase Gradient

VIDEO-SHOT TRANSITION DETECTION: A SPATIO-TEMPORAL SALIENCY APPROACH

2010 ◽  
Vol 24 (08) ◽  
pp. 1295-1309 ◽  
Author(s):  
XIAN WU ◽  
JIANHUANG LAI ◽  
PONG C. YUEN
Keyword(s):  
Error Probability ◽  
Spatial Information ◽  
Saliency Map ◽  
Detection Error ◽  
Novel Approach ◽  
Video Shot ◽  
Recent Method ◽  
Temporal And Spatial ◽  
Spatio Temporal ◽  
Shot Transitions

This paper proposes a novel approach for video-shot transition detection using spatio-temporal saliency. Both temporal and spatial information are combined to generate a saliency map, and features are available based on the change of saliency. Considering the context of shot changes, a statistical detector is constructed to determine all types of shot transitions by the minimization of the detection-error probability simultaneously under the same framework. The evaluation performed on videos of various content types demonstrates that the proposed approach outperforms a more recent method and two publicly available systems, namely VideoAnnex and VCM.

Detecting land deformation due to groundwater changes with InSAR observations - the case of the island of Gotland, Sweden

2021 ◽  
Author(s):  
Mehdi Darvishi ◽  
Fernando Jaramillo
Keyword(s):  
Land Subsidence ◽  
Groundwater Level ◽  
Ground Deformation ◽  
Soil Depth ◽  
Ground Surface ◽  
Groundwater Depletion ◽  
Groundwater Levels ◽  
Small Baseline Subset ◽  
Small Baseline ◽  
The Baltic

<p>In the recent years, southern Sweden has experienced drought conditions during the summer with potential risks of groundwater shortages. One of the main physical effects of groundwater depletion is land subsidence, a geohazard that potentially damages urban infrastructure, natural resources and can generate casualties. We here investigate land subsidence induced by groundwater depletion and/or seasonal variations in Gotland, an agricultural island in the Baltic Sea experiencing recent hydrological droughts in the summer. Taking advantage of the multiple monitoring groundwater wells active on the island, we explore the existence of a relationship between groundwater fluctuations and ground deformation, as obtained from Interferometric Synthetic Aperture Radar (InSAR). The aim in the long-term is to develop a high-accuracy map of land subsidence with an appropriate temporal and spatial resolution to understand groundwater changes in the area are recognize hydroclimatic and anthropogenic drivers of change.</p><p>We processed Sentinel-1 (S1) data, covering the time span of 2016-2019, by using the Small BAseline Subset (SBAS) to process 119 S1-A/B data (descending mode). The groundwater level of Nineteen wells distributed over the Gotland island were used to assess the relationship between groundwater depletion and the detected InSAR displacement. In addition to that, the roles of other geological key factors such as soil depth, ground capacity in bed rock, karstification, structure of bedrock and soil type in occurring land subsidence also investigated. The findings showed that the groundwater level in thirteen wells with soil depths of less than 5 meters correlated well with InSAR displacements. The closeness of bedrock to ground surface (small soil depth) was responsible for high coherence values near the wells, and enabled the detection land subsidence. The results demonstrated that InSAR could use as an effective monitoring system for groundwater management and can assist in predicting or estimating low groundwater levels during summer conditions.</p>

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