The Sentinel-1 constellation for InSAR applications: Experiences from the InSARAP project

Larsen, Yngvar; Marinkovic, Petar; Dehls, John; Perski, Zbigniew; Hooper, Andrew; Wright, Tim

doi:10.1109/igarss.2017.8128260

Cited by 4 publications

(4 citation statements)

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“…The requirement of an accuracy of 1 mm/y at more that 100 km (<10 nstrain) pushes the technique to its limits [5]. Notwithstanding, it has been demonstrated that, since actual SAR missions are characterized by very stable oscillators [31] and very good orbit knowledge [32,33], such numbers can be considered achievable. The major limitation is atmospheric effects.…”

Section: North Anatolian Fault Datasetmentioning

confidence: 99%

A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate Measurements

2020

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This paper deals with the integration of deformation rates derived from Synthetic Aperture Radar Interferometry (InSAR) and Global Navigation Satellite System (GNSS) data. The proposed approach relies on knowledge of the variance/covariance of both InSAR and GNSS measurements so that they may be combined accounting for the spectral properties of their errors, hence preserving all spatial frequencies of the deformation detected by the two techniques. The variance/covariance description of the output product is also provided. A performance analysis is carried out on realistic simulated scenarios in order to show the boundaries of the technique. The proposed approach is finally applied to real data. Five Sentinel-1A/B stacks acquired over two different areas of interest are processed and discussed. The first example is a merged deformation map of the northern part of the Netherlands for both ascending and descending geometries. The second example shows the deformation at the junction between the North and East Anatolian Fault using three consecutive descending stacks.

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Section: North Anatolian Fault Datasetmentioning

confidence: 99%

A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate Measurements

2020

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“…For example, a strong bias was observed due to an oscillator drift on the Envisat ASAR data (Marinkovic & Larsen, 2013). However, the S1 oscillator appears very stable (Larsen et al., 2017). A multi‐annual TEC change or TEC gradient change could also produce a bias, which could be avoided with GIM‐derived TEC corrections when validated (see subsection 6.3).…”

Section: Discussionmentioning

confidence: 99%

Referencing of Continental‐Scale InSAR‐Derived Velocity Fields: Case Study of the Eastern Tibetan Plateau

et al. 2023

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The ever-increasing temporal resolution and spatial coverage of radar interferometry (InSAR) satellite data has expanded the application fields of InSAR. For tectonic studies of active faulting and continental-scale deformation, the use of InSAR has gradually evolved from local-scale studies of earthquakes and fault seismic cycle (e.g., Bürgmann et al., 2000;Massonnet et al., 1993) to analyzes at the large-scale of major fault systems and plate-tectonics (e.g.,

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“…a typical swath of future spaceborne SAR's. Fortunately, with Sentinel-1, the drifts are smaller than 10 −9 /year [2] and they can be ignored. One must say that if the oscillator drift can be well modeled, the magnitude of the drift is not decisive but its knowledge is then the crucial point.…”

Section: Instrument and Geometrymentioning

confidence: 99%

Insar Error Budget for Large Scale Deformation

Zan

Parizzi

González

et al. 2019

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium

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The capacity of SAR interferometry to measure surface deformation with accuracy of 1 mm/year or better are well known. However this is typically limited to relative motion at short distance. Thanks to several advances in SAR sensor quality, data availability, orbit determination, processing, and calibration of atmospheric delays it is now possible to achieve that accuracy even across large distances of hundreds of kilometers. In this paper we revise the main contributions to the large scale error, considering available mitigation techniques. We provide a first validation for a processing based on Sentinel-1 data, by comparing our results with GNSS stations. For future SAR's operating at lower frequencies, it is vital to consider ionospheric corrections and likely also the influence of moisture variations in natural scatterers. The choice of processing algorithms, though typically not discussed, can also have a significant effect on the quality of the result.

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The Sentinel-1 constellation for InSAR applications: Experiences from the InSARAP project

Cited by 4 publications

References 1 publication

A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate Measurements

A Covariance-Based Approach to Merging InSAR and GNSS Displacement Rate Measurements

Referencing of Continental‐Scale InSAR‐Derived Velocity Fields: Case Study of the Eastern Tibetan Plateau

Insar Error Budget for Large Scale Deformation

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