Ground Displacement Measurement by TerraSAR-X Image Correlation: The 2011 Tohoku-Oki Earthquake

Yague-Martinez, Nestor; Eineder, Michael; Cong, Xiaoying; Minet, Christian

doi:10.1109/lgrs.2012.2196020

Cited by 28 publications

(14 citation statements)

References 8 publications

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“…[3][4][5][6][7][8][9][10] The method is beneficial for monitoring topographic changes when using the DInSAR or the absolute ranging technique. 11 Cong et al 12 correspondingly demonstrated a straightforward technique exclusively using the ECMWF ERAinterim data, which is a global assimilation data product. In contrast to that technique, the NWP product-related technique enables physical interpolation between time steps based on a physical model of the atmosphere.…”

Section: Introductionmentioning

confidence: 99%

Spin-up time research on the weather research and forecasting model for atmospheric delay mitigations of electromagnetic waves

Ulmer

Balss

2016

J. Appl. Remote Sens

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Abstract. Atmosphere causes distortions in the geometry and phases of synthetic aperture radar images denoted by the atmospheric phase screen (APS). Numerical weather models are beneficial in correcting these disturbances. After initialization, the models need time to derive a physical valid state. This is called the spin-up time, and it affects delay predictions. The positive impact of a 12-h spin-up time on delay mitigation has not yet been reported and is the objective of this paper. Hence, four independent experiments are considered, revealing the best accuracy in the case of 12-h predictions and showing the best consistency of spatial frequencies. First, global positioning system zenith path delay (ZPD) series are compared with model-predicted ZPD series, which reports a 28% reduction of the root mean squared error. Second, the absolute ranging technique as an application of the delay prediction reports a 21% standard deviation decrease of position estimates. Third, a comparison of spatial frequencies between APS predictions and interferograms shows a closer consistency using a 12-h rather than a 6-h spin-up time. Fourth, APS mitigation in interferograms as an application of APS prediction is twice as good with respect to the 12-h spin-up time as with the 6-h spin-up time. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Section: Introductionmentioning

confidence: 99%

Spin-up time research on the weather research and forecasting model for atmospheric delay mitigations of electromagnetic waves

Ulmer

Balss

2016

J. Appl. Remote Sens

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“…[3][4][5][6][7] Similar to DInSAR, the delay correction using NWPs is also beneficial for the absolute ranging technique to estimate displacement maps. 8 Cong et al 9 demonstrated a straightforward technique by using exclusively the European Centre for Medium-Range Weather Forecasts reanalysis (ECMWF ERA-interim) data, which are also used for the NWP initialization in this work. In comparison to this technique, the model-based prediction technique enables the physical interpolation between time steps.…”

Section: Introductionmentioning

confidence: 99%

On the accuracy gain of electromagnetic wave delay predictions derived by the digital filter initialization technique

Ulmer

2016

J. Appl. Remote Sens

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Abstract. Atmosphere causes delay distortions in synthetic aperture radar images. Numerical weather prediction models, which compute the forecast stepwise, are beneficial in correcting this distortion. After initialization, the model needs time to reach a balanced state, such that first prediction steps contain errors. The imbalance causes false predicted precipitation, which then affects the water vapor distribution. Correspondingly, the predicted zenith path delay (ZPD), which depends on this distribution, is affected by the initial imbalances. The digital filtering initialization (DFI) technique reduces these imbalances and the ZPD prediction disturbances, respectively. The objective of this paper is the accuracy gain for ZPD predictions, which is achieved by this technique. For the accuracy gain investigation, predicted ZPD time series of the weather research and forecasting (WRF) model with and without DFI are compared against Global Navigation Satellite System (GNSS)-derived time series from 233 GNSS stations mainly located in Germany. Three conclusions are found. First, the experiment confirms that the DFI technique improves the precipitation forecast. Second, the corresponding accuracy gain, i.e., the bias of ZPD predictions, improves by about 13%. Third, the accuracy gain is only valid for the first 4 h of the prediction.

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“…For instance, many researchers used SAR data for their studies for the Great East Japan Earthquake 2011, which occurred on March 11, 2011, and estimated the flooded area (Park et al, 2013), damaged buildings (Gokon and Koshimura, 2012), and ground displacement (Yague-Martinez et al, 2012). Interferometric synthetic-aperture radar (InSAR) is a wellestablished technique to estimate the centimetre order displacement using phase information (Gabriel et al, 1989), though the displacement is saturated when the gradient of the displacement exceeds half a fringe per pixel.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Relative Geometric Accuracy of Terrasar-X by Pixel Matching Methodology

Nonaka¹,

Asaka²,

Iwashita³

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Recently, high-resolution commercial SAR satellites with several meters of resolutions are widely utilized for various applications and disaster monitoring is one of the commonly applied areas. The information about the flooding situation and ground displacement was rapidly announced to the public after the Great East Japan Earthquake 2011. One of the studies reported the displacement in Tohoku region by the pixel matching methodology using both pre-and post-event TerraSAR-X data, and the validated accuracy was about 30 cm at the GEONET reference points. In order to discuss the spatial distribution of the displacement, we need to evaluate the relative accuracy of the displacement in addition to the absolute accuracy. In the previous studies, our study team evaluated the absolute 2D geo-location accuracy of the TerraSAR-X ortho-rectified EEC product for both flat and mountain areas. Therefore, the purpose of the current study was to evaluate the spatial and temporal relative geo-location accuracies of the product by considering the displacement of the fixed point as the relative geo-location accuracy. Firstly, by utilizing TerraSAR-X StripMap dataset, the pixel matching method for estimating the displacement with sub-pixel level was developed. Secondly, the validity of the method was confirmed by comparing with GEONET data. We confirmed that the accuracy of the displacement for X and Y direction was in agreement with the previous studies. Subsequently, the methodology was applied to 20 pairs of data set for areas of Tokyo Ota-ku and Kawasaki-shi, and the displacement of each pair was evaluated. It was revealed that the time series displacement rate had the seasonal trend and seemed to be related to atmospheric delay.

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Ground Displacement Measurement by TerraSAR-X Image Correlation: The 2011 Tohoku-Oki Earthquake

Cited by 28 publications

References 8 publications

Spin-up time research on the weather research and forecasting model for atmospheric delay mitigations of electromagnetic waves

Spin-up time research on the weather research and forecasting model for atmospheric delay mitigations of electromagnetic waves

On the accuracy gain of electromagnetic wave delay predictions derived by the digital filter initialization technique

Evaluation of Relative Geometric Accuracy of Terrasar-X by Pixel Matching Methodology

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