High‐Resolution Interseismic Strain Mapping From InSAR Phase‐Gradient Stacking: Application to the North Anatolian Fault With Implications for the Non‐Uniform Strain Distribution Related to Coseismic Slip Distribution

Liu, Ziming; Wang, Teng

doi:10.1029/2023gl104168

Cited by 4 publications

(3 citation statements)

References 54 publications

(128 reference statements)

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“…The application of the range and azimuth direction to seismic fault zones and active faults has been investigated [26][27][28], but the detection of landslides using only the range or azimuthal direction is subject to partial erroneous detection of landslides [34]. This is mainly due to the fact that gradients mainly detect boundary information, so landslides with deformation appear as two neighboring regions in the detection results of a single direction phase gradient stacking [34], which leads to a situation where some landslides are not signaled in one direction but are signaled in other directions.…”

Section: Comparison Of Range and Azimuth Phase Gradient Stackingmentioning

confidence: 99%

“…The phase gradient method is gradually being used to locate deformation regions. It has been used to detect the deformation information associated with seismic fault zones [26,27] and faults [28]. The deformation range caused by these cases is relatively large, often extending for thousands or tens of kilometers in space, and these regions can be identified by the phase gradient method.…”

Section: Introductionmentioning

confidence: 99%

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Landslide Detection Based on Multi-Direction Phase Gradient Stacking, with Application to Zhouqu, China

Xiong,

Sun,

2024

Applied Sciences

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Landslides are a common geological disaster, which cause many economic losses and casualties in the world each year. Drawing up a landslide list and monitoring their deformations is crucial to prevent landslide disasters. Interferometric synthetic aperture radar (InSAR) can obtain millimeter-level surface deformations and provide data support for landslide deformation monitoring. However, some landslides are difficult to detect due to the low-coherence caused by vegetation cover in mountainous areas and the difficulty of phase unwrapping caused by large landslide deformations. In this paper, a method based on multi-direction phase gradient stacking is proposed. It employs the differential interferograms of small baseline sets to directly obtain the abnormal region, thereby avoiding the problem where part of landslide cannot be detected due to a phase unwrapping error. In this study, the Sentinel-1 satellite ascending and descending data from 2018 to 2020 are used to detect landslides around Zhouqu County, China. A total of 26 active landslides were detected in ascending data and 32 active landslides in the descending data using the method in this paper, while the SBAS-InSAR detected 19 active landslides in the ascending data and 25 active landslides in the descending data. The method in this paper can successfully detect landslides in areas that are difficult for the SBAS-InSAR to detect. In addition, the proposed method does not require phase unwrapping, so a significant amount of data processing time can be saved.

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Section: Comparison Of Range and Azimuth Phase Gradient Stackingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Landslide Detection Based on Multi-Direction Phase Gradient Stacking, with Application to Zhouqu, China

Xiong,

Sun,

2024

Applied Sciences

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show abstract

“…Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) have been widely used to map large‐scale tectonic deformation and strain accumulation along active faults in actively deforming regions, such as, the North Anatolian fault, the Pamir convergent belt, and the San Andreas fault (Bletery et al., 2020; Fialko, 2006; Hussain et al., 2018; Jolivet et al., 2023; Y. X. Li et al., 2023; Liu & Wang, 2023; Metzger et al., 2021; Rousset et al., 2016; Weiss et al., 2020; Xu et al., 2021). Here, we combine GNSS and InSAR to obtain 3D surface deformation rate maps with minimized rate offsets across adjacent InSAR swaths.…”

Section: Introductionmentioning

confidence: 99%

Present‐Day 3D Crustal Deformation of the Northeastern Tibetan Plateau From Space Geodesy

Wu,

Ge,

Liu

et al. 2024

Geophysical Research Letters

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High‐resolution present‐day earth surface deformation maps from satellites provide important data constraints, which help us better understand tectonic processes and analyze seismic hazards. Here, we use Sentinel‐1 Radar images (2014–2020) and accurate positioning measurements (2009–2019) to get a high‐resolution three‐dimensional earth surface velocity map for the northeastern Tibetan Plateau, and we invert the slip rate and coupling ratio of major regional faults. We find ∼4 mm/yr uplift along an arc from the Qilianshan to Lajishan, relative to the neighboring low‐elevation area to the east, which indicates ongoing rapid orogeny. We find transient deformation along the Laohushan and 1920 M8.5 Haiyuan rupture segments of the Haiyuan fault, whereas the western Haiyuan, southern Liupanshan, central Lajishan and central‐western West Qinling faults are essentially locked above 15–20 km, suggesting a potentially high seismic hazard.

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InSAR phase gradient reveals fault‐zone controls on the spatial distribution of slow‐moving landslides in the active orogenic region of Hazara‐Kashmir, Pakistan

Ahmad,

Fu,

Wang

2024

Earth Surf Processes Landf

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Slow‐moving landslides play important roles in the landscape evolution and hazards planning. Studies along some strike‐slip faults have shown that the geological structures and bed‐rock lithology significantly contribute the distribution of slow‐moving landslides. However, controls on the distribution of slow‐moving landslides are poorly constrained in active orogenic regions, hindering our understanding of its role in the rapid orogenic process. The Hazara Kashmir Syntaxis in Pakistan is such a prominent geological structure of lesser Himalaya, where the inventory of slow‐moving landslides is scarce. Here, we attempt the interferometric synthetic aperture radar phase‐gradient stacking coupled with a deep‐learning system to provide the first slow‐moving landslides inventory (1066 presently active landslides, 2016–2023) in the Hazara‐Kashmir region. Along with optical imagery and field investigations, we analyse the impacts of fault structures, bed‐rock lithology, topography along with spatial distribution of earthquake and precipitation on the distribution of these slow‐moving landslides. We find that 33% of the detected slow‐moving landslides are distributed within 1000 m to active faults, and show a decreasing trend moving away from fault zones. This pattern strongly suggests that the active thrusting faults in this region significantly controls the distribution of slow‐moving landslides, while topography and precipitation show less impacts. Our study reveals the spatial distribution of slow‐moving landslides in a tectonic complex region with rapid orogenic process, and thus shows potential implications in geomorphology modelling and hazards evaluation for many less‐monitored, contemporary uplifting high‐mountain regions.

show abstract

High‐Resolution Interseismic Strain Mapping From InSAR Phase‐Gradient Stacking: Application to the North Anatolian Fault With Implications for the Non‐Uniform Strain Distribution Related to Coseismic Slip Distribution

Cited by 4 publications

References 54 publications

Landslide Detection Based on Multi-Direction Phase Gradient Stacking, with Application to Zhouqu, China

Landslide Detection Based on Multi-Direction Phase Gradient Stacking, with Application to Zhouqu, China

Present‐Day 3D Crustal Deformation of the Northeastern Tibetan Plateau From Space Geodesy

InSAR phase gradient reveals fault‐zone controls on the spatial distribution of slow‐moving landslides in the active orogenic region of Hazara‐Kashmir, Pakistan

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