Post-Eruptive Inflation of Okmok Volcano, Alaska, from InSAR, 2008–2014

Qu, Feifei; Lü, Zhong; Poland, Michael P.; Freymueller, J. T.; Zhang, Qin; Jung, Hyung-Sup

doi:10.3390/rs71215839

Cited by 15 publications

(22 citation statements)

References 40 publications

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“…The Okmok test site has a dominant deformation source from the underlying volcanic pressure system [54][55][56], but also contains localized surface subsidence in a limited region inside the caldera due to the contraction of a lava flow post-emplacement [54,57]. Previous studies [47,58] [46].…”

Section: Geodetic Setting Of Study Areas and Sar Imagerymentioning

confidence: 99%

Comparison of Small Baseline Interferometric SAR Processors for Estimating Ground Deformation

et al. 2016

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Abstract:The small Baseline Synthetic Aperture Radar (SAR) Interferometry (SBI) technique has been widely and successfully applied in various ground deformation monitoring applications. Over the last decade, a variety of SBI algorithms have been developed based on the same fundamental concepts. Recently developed SBI toolboxes provide an open environment for researchers to apply different SBI methods for various purposes. However, there has been no thorough discussion that compares the particular characteristics of different SBI methods and their corresponding performance in ground deformation reconstruction. Thus, two SBI toolboxes that implement a total of four SBI algorithms were selected for comparison. This study discusses and summarizes the main differences, pros and cons of these four SBI implementations, which could help users to choose a suitable SBI method for their specific application. The study focuses on exploring the suitability of each SBI module under various data set conditions, including small/large number of interferograms, the presence or absence of larger time gaps, urban/vegetation ground coverage, and temporally regular/irregular ground displacement with multiple spatial scales. Within this paper we discuss the corresponding theoretical background of each SBI method. We present a performance analysis of these SBI modules based on two real data sets characterized by different environmental and surface deformation conditions. The study shows that all four SBI processors are capable of generating similar ground deformation results when the data set has sufficient temporal sampling and a stable ground backscatter mechanism like urban area. Strengths and limitations of different SBI processors were analyzed based on data set configuration and environmental conditions and are summarized in this paper to guide future users of SBI techniques.

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Section: Geodetic Setting Of Study Areas and Sar Imagerymentioning

confidence: 99%

Comparison of Small Baseline Interferometric SAR Processors for Estimating Ground Deformation

et al. 2016

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“…Thus, the difference in the constant components of the TECs only gives rise to a fixed bias in the interferometric phase. In contrast, the variations of DTEC0=10TECU, Dk1=1e-5TECU/s,Dk2=1e-5TECU/s2 DTEC0=20TECU, Dk1=1e-5TECU/s,Dk2=1e-5TECU/s2 DTEC0=10TECU, Dk1=1e-3TECU/s,Dk2=1e-5TECU/s2 DTEC0=10TECU, Dk1=2e-3TECU/s,Dk2=1e-5TECU/s2 DTEC0=10TECU, Dk1=1e-5TECU/s,Dk2=1e-4TECU/s2 DTEC0=10TECU, Dk1=1e-5TECU/s,Dk2=2e-4TECU/s2 Utilizing the USTEC data in Figure 4 and Equation (14), the interferometric phase screen errors generated by Φ 1 (P) and Φ 2 (P) are shown in Figure 7a. The spatial distributed fringe frequency is brought by the interferometric phase screen ranges from less than one circle to multiple circles per one million square kilometers.…”

Section: Interferometric Phase Screen Errormentioning

confidence: 99%

“…Therefore, some compensation algorithms based on Persistent Scatterer technology (PS) [4,[33][34][35][36][37] or some similar methods based on the high quality coherent points are really needed to eliminate the serious impacts of the interferometric phase screen errors brought by the temporal-spatial background ionosphere variation in GEO D-InSAR processing in the future. Utilizing the USTEC data in Figure 4 and Equation (14), the interferometric phase screen errors generated by 1 ( ) Φ P  and 2 ( ) Φ P  are shown in Figure 7a. The spatial distributed fringe frequency is brought by the interferometric phase screen ranges from less than one circle to multiple circles per one million square kilometers.…”

Section: Interferometric Phase Screen Errormentioning

confidence: 99%

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Impacts of Temporal-Spatial Variant Background Ionosphere on Repeat-Track GEO D-InSAR System

Dong

et al. 2016

Remote Sensing

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An L band geosynchronous synthetic aperture radar (GEO SAR) differential interferometry system (D-InSAR) will be obviously impacted by the background ionosphere, which will give rise to relative image shifts and decorrelations of the SAR interferometry (InSAR) pair, and induce the interferometric phase screen errors in interferograms. However, the background ionosphere varies within the long integration time (hundreds to thousands of seconds) and the extensive imaging scene (1000 km levels) of GEO SAR. As a result, the conventional temporal-spatial invariant background ionosphere model (i.e., frozen model) used in Low Earth Orbit (LEO) SAR is no longer valid. To address the issue, we firstly construct a temporal-spatial background ionosphere variation model, and then theoretically analyze its impacts, including relative image shifts and the decorrelation of the GEO InSAR pair, and the interferometric phase screen errors, on the repeat-track GEO D-InSAR processing. The related impacts highly depend on the background ionosphere parameters (constant total electron content (TEC) component, and the temporal first-order and the temporal second-order derivatives of TEC with respect to the azimuth time), signal bandwidth, and integration time. Finally, the background ionosphere data at Isla Guadalupe Island (29.02 • N, 118.27 • W) on 7-8 October 2013 is employed for validating the aforementioned analysis. Under the selected background ionosphere dataset, the temporal-spatial background ionosphere variation can give rise to a relative azimuth shift of dozens of meters at most, and even the complete decorrelation in the InSAR pair. Moreover, the produced interferometric phase screen error corresponds to a deformation measurement error of more than 0.2 m at most, even in a not severely impacted area.

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“…Recently, Interferometric Synthetic Aperture Radar (InSAR) has been used as a routine tool in monitoring ground deformations associated with geohazards such as earthquake [1], volcano eruption [2], glacier movement [3], and landslide [4]. With the appearance of a number of multitemporal InSAR (MT-InSAR) algorithms [5][6][7][8][9], the inherent errors (i.e., decorrelation noises, topographic residuals, orbital ramps, and atmospheric artifacts) in the differential InSAR (DInSAR) measurements can be well suppressed by analyzing a time series of SAR datasets.…”

Section: Introductionmentioning

confidence: 99%

Estimating Actual 2D Ground Deformations Induced by Underground Activities with Cross-Heading InSAR Measurements

Xiao-ying

Sun

2017

Journal of Sensors

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InSAR can only monitor relative ground deformations with respect to a reference area. In order to obtain actual deformations, GCPs or stable area is required in the study area, which, however, may be unavailable in the investigating of geohazards associated with underground activities (i.e., groundwater pumping, underground mining, and oil/gas exploitation). We propose a novel approach to estimate actual 2D deformations based on the InSAR relative LOS measurements acquired from cross-heading datasets. The errors induced by the arbitrary selection of reference areas can thus be avoided. The performance of the proposed approach is validated by a series of simulations. By providing the ascending and descending measurements with errors of 2 and 1.5 mm/year STDs, respectively, the RMSEs are 2.1 and 2.6 mm/year for the estimated vertical and east deformations, respectively. A case study is carried out in Cangzhou, China, for estimating the actual 2D ground deformations associated with groundwater pumping. By integrating ALOS ascending and ENVISAT descending datasets acquired between 2007 and 2010, we found that the Cangzhou area experienced ground subsidence of up to 23.4 mm/year in the suburbs but ground uplift of up to 20.9 mm/year in the urban area, both of which are accompanied by considerable lateral deformations.

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Post-Eruptive Inflation of Okmok Volcano, Alaska, from InSAR, 2008–2014

Cited by 15 publications

References 40 publications

Comparison of Small Baseline Interferometric SAR Processors for Estimating Ground Deformation

Comparison of Small Baseline Interferometric SAR Processors for Estimating Ground Deformation

Impacts of Temporal-Spatial Variant Background Ionosphere on Repeat-Track GEO D-InSAR System

Estimating Actual 2D Ground Deformations Induced by Underground Activities with Cross-Heading InSAR Measurements

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