Horizontal coseismic deformation of the 2003 Bam (Iran) earthquake measured from SPOT‐5 THR satellite imagery

Binet, Renaud; Bollinger, Laurent

doi:10.1029/2004gl021897

Cited by 48 publications

(35 citation statements)

References 12 publications

(18 reference statements)

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“…The technique is now widely used to monitor the earth surface changes and dynamics [8][9][10][11][12][13][14][15]. As richer and constantly updated satellite observation data become available, the application of optical images cross-correlation technique has been expanded to fields such as glacier flow velocity extraction [10][11][12], quantification of sand dune migration [13][14][15], terrain-deformation measurements of slow landslides [16], monitoring process of significant rift events [17], volcanic monitoring [18] and particularly extensive coseismic deformation extraction [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

“…Many studies demonstrate that the Landsat 8 image cross-correlation technique has advantages in measuring surface deformation, such as mapping ice sheet velocity [26], coseismic deformation extraction [25,[27][28][29] and volcano deformation monitoring [30]. Many researchers have done a lot of analyses and error source correction of displacement measurement, but they mainly focused on a few data sources, such as SPOT, ASTER, HiRISE (High Resolution Imaging Science Experiment) and aerial imagery [3,8,11,[13][14][15][16][17][19][20][21]31,32]. In general, the deformation field obtained by different types of optical sensors with cross-correlation technique has disparities in error structure and magnitude level.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements

et al. 2016

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Abstract:Because of the advantages of low cost, large coverage and short revisit cycle, Landsat 8 images have been widely applied to monitor earth surface movements. However, there are few systematic studies considering the error source characteristics or the improvement of the deformation field accuracy obtained by Landsat 8 image. In this study, we utilize the 2013 Mw 7.7 Balochistan, Pakistan earthquake to analyze error spatio-temporal characteristics and elaborate how to mitigate error sources in the deformation field extracted from multi-temporal Landsat 8 images. We found that the stripe artifacts and the topographic shadowing artifacts are two major error components in the deformation field, which currently lack overall understanding and an effective mitigation strategy. For the stripe artifacts, we propose a small spatial baseline (<200 m) method to avoid the stripe artifacts effect on the deformation field. We also propose a small radiometric baseline method to reduce the topographic shadowing artifacts and radiometric decorrelation noises. Those performances and accuracy evaluation show that these two methods are effective in improving the precision of deformation field. This study provides the possibility to detect subtle ground movement with higher precision caused by earthquake, melting glaciers, landslides, etc., with Landsat 8 images. It is also a good reference for error source analysis and corrections in deformation field extracted from other optical satellite images.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements

et al. 2016

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“…Of course state of the art methods propose various ad-hoc indicators of local correlation or matching quality as in [3], but we wish to propose a quantitative error estimate rather than qualitative measures that are, in practice, difficult to interpret. We keep in mind the use of the estimated deformation fields as inputs to a subsequent analysis algorithms (for instance inversion methods to derive the 3D fault structure and coseismic slip distribution from surface displacements in the case of earthquakes).…”

Section: Introductionmentioning

confidence: 99%

Inferring Deformation Fields from Multidate Satellite Images

Jalobeanu¹,

Fitzenz²

2008

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium

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We focus on a geophysical application of image processing: the measurement of high resolution ground deformation from two optical satellite images taken at different dates. Disparity maps estimated from image pairs usually lack quantitative error estimates. This is a major issue for measuring physical parameters, such as ground deformation or topography variations. Thus, we propose a new method to infer the disparity map. We adopt a probabilistic approach, treating all parameters as random variables, which provides a rigorous framework for parameter estimation and uncertainty evaluation. We start by defining a generative model of the data given all model variables. This forward model consists of warping the scene using B-Splines and applying a spatially adaptive radiometric change map. Then we use Bayesian inference to invert and recover the a posteriori probability density function (pdf) of the disparity map. The method is validated on multidate SPOT 5 imagery related to the Bam earthquake (Iran), showing results compatible with INSAR measurements.

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“…fault mechanics and geometry), future earthquake recurrence and seismic hazard assessment (Leprince et al, 2007;Kaneda et al, 2008). Moreover, these measurements also assist in interpretation of morphotectonic features in other earthquake prone areas for preparing seismic hazard maps (Binet and Bollinger, 2005;Kaneda et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…Using remote sensing data, displacement field can be measured by comparison of pre-and post-earthquake images. These displacements can be calculated either by using Synthetic Aperture Radar (SAR) Interferometry (Massonnet et al, 1993;Taylor et al, 2008) or by offsets tracking with sub-pixel correlation of SAR amplitude Fialko et al, 2005;Pathier et al, 2006) or optical images (Crippen, 1992;van Puymbroeck et al, 2000;Dominguez et al, 2003;Binet and Bollinger, 2005;Leprince et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Geostatistical and space geodetic methods on a 3D coseismic displacement field

Yaseen¹

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SummaryCoseismic displacements at the Earth's surface arise due to the release of energy by earthquakes. The energy, and hence the amount of displacement, depends mainly on the magnitude, depth and the movement mechanism of an earthquake. Coseismic displacements play a vital role in the characterization of geological faults and understanding of earthquake dynamics. This understanding is based in turn on the accurate measurement of coseismic displacements and creation of a continuous-field displacement map. The main objective of this research was to measure the coseismic displacements and to construct a 3D coseismic displacement field for an earthquake.Displacements are typically measured by comparing pre-and postearthquake radar images. In this study InSAR is used that measures phase (time) differences between pre-and post-earthquake SAR images resulting in displacements into line-of-sight (LOS) direction. The LOS is mainly sensitive in the vertical direction, moderately in the across flight direction and insensitive in the along flight direction. To measure the along-flight displacement component pixel tracking was used, providing azimuth offsets (AZO). Pixel tracking correlates the coregistered pre-and post-earthquake optical or SAR images. In this study pixel tracking was used for both SAR and optical data, whereas InSAR is used for SAR data only. Using the obtained displacement results, a 3D displacement field was generated from both descending and ascending image pairs bracketing the earthquake event.The study considered the 2003 Bam earthquake. The city is located on a geological fault that caused occurrence of the earthquake. From the measured displacements it appeared that the major part of the fault is located south of the city. It has a length of 13 km and the fault strike equals 170º, close to the along flight direction. The major vertical displacement occurred on east of the fault, showing a uplift in the south-eastern part of displacement map and subsidence in its north-eastern part. Horizontal displacements showed a relative movement along the fault in the along flight direction. The displacement was greater in horizontal direction than the LOS, revealing that the earthquake causative fault is a strike-slip fault.A displacement map commonly contains missing coseismic values due to lack of coherence between SAR images. In this study, missing displacement values were caused by non-coherence of pre-and post-earthquake SAR images for the area affected by the earthquake. These missing displacement values may be important for fault characterization, in particular if they occur along the earthquake-causative geological fault. Missing values were interpolated to evaluate the continuity of the earthquake causative fault underneath the city of Bam. i To assess the accuracy of the interpolated coseismic values, subsets of missing co-seismic values were selected and translated towards locations where displacement values exist. Here, missing values were generated artificially. These values were interpolate...

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Horizontal coseismic deformation of the 2003 Bam (Iran) earthquake measured from SPOT‐5 THR satellite imagery

Cited by 48 publications

References 12 publications

Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements

Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements

Inferring Deformation Fields from Multidate Satellite Images

Geostatistical and space geodetic methods on a 3D coseismic displacement field

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