Continuous geodetic measurements in landslide prone regions are necessary to avoid disasters and better understand the spatiotemporal and kinematic evolution of landslides. The detection and characterization of landslides in high alpine environments remains a challenge associated with difficult accessibility, extensive coverage, limitations of available techniques, and the complex nature of landslide process. Recent studies using space-based observations and especially Persistent Scatterer Interferometry (PSI) techniques with the integration of in-situ monitoring instrumentation are providing vital information for an actual landslide monitoring. In the present study, the Stanford Method for Persistent Scatterers InSAR package (StaMPS) is employed to process the series of Sentinel 1-A and 1-B Synthetic Aperture Radar (SAR) images acquired between 2015 and 2019 along ascending and descending orbits for the selected area in the French Alps. We applied the proposed approach, based on extraction of Active Deformation Areas (ADA), to automatically detect and assess the state of activity and the intensity of the suspected slow-moving landslides in the study area. We illustrated the potential of Sentinel-1 data with the aim of detecting regions of relatively low motion rates that be can attributed to activate landslide and updated pre-existing national landslide inventory maps on a regional scale in terms of slow moving landslides. Our results are compared to pre-existing landslide inventories. More than 100 unknown slow-moving landslides, their spatial pattern, deformation rate, state of activity, as well as orientation are successfully identified over an area of 4000 km² located in the French Alps. We also address the current limitations due the nature of PSI and geometric characteristic of InSAR data for measuring slope movements in mountainous environments like Alps.

Characterizing the spatiotemporal evolution of creep is essential to constrain fault slip budget and understand creep mechanism. Studies based on interferometric synthetic aperture radar and Global Positioning System (GPS) satellite observations until 2012 have shown that the central segment of the 17 August 1999 M_w 7.4 Izmit earthquake on the North Anatolian Fault began slipping aseismically following the event. In the present study, we combine new interferometric synthetic aperture radar time series, based on TerraSAR‐X and Sentinel 1A/B radar images acquired over the period 2011–2017, with near‐field GPS measurement campaigns performed every 6 months from 2014 to 2016. The mean velocity fields reveal that creep on the central segment of the 1999 Izmit fault rupture continues to decay, more than 19 years after the earthquake, in overall agreement with models of postseismic afterslip decaying logarithmically with time for a long period of time. Along the fault section that experienced supershear velocity rupture during the Izmit earthquake creep continues with a rate up to ~ 8 mm/year. A significant transient accelerating creep is detected in December 2016 on the Sentinel‐1 time series, near the maximum creep rate location, associated with a total surface slip of 10 mm released in 1 month only. Additional analyses of the vertical velocity fields show a persistent subsidence on the hanging wall block of the Golcuk normal fault that also ruptured during the Izmit earthquake. Our results demonstrate that afterslip processes along the North Anatolian Fault east‐southeast of Istanbul are more complex than previously proposed as they vary spatiotemporally along the fault.

We characterize and monitor subsidence of the Bursa Plain (southern Marmara region of Turkey), which has been interpreted as resulting from tectonic motions in the region. We quantify the subsidence using Interferometric Synthetic Aperture Radar (InSAR) time-series analysis. The Stanford Method for Persistent Scatterers InSAR package (StaMPS) is employed to process series of Sentinel 1 A-B radar images acquired between 2014 and 2017 along both ascending and descending orbits. The vertical velocity field obtained after decomposition of line-of-sight velocity fields on the two tracks reveals that the Bursa plain is subsiding at rates up to 25 mm/yr. The most prominent subsidence signal in the basin forms an east-west elongated ellipse of deformation in the east, and is bounded by a Quaternary alluvial plain undergoing average vertical subsidence at ~10 mm/yr. Another localized subsidence signal is located 5 km north of the city, following the Bursa alluvial fan, and is subsiding at velocities up to 25 mm/yr. The comparison between temporal variations of the subsiding surface displacements and variations of the water pressure head in the aquifer allows estimation of the compressibility of the aquifer, $\alpha$ . It falls in the range of $0.5\times {10}^{-6}-2\times {10}^{-6}$ Pa⁻¹, which corresponds to typical values for clay and sand sediments. We find a clear correlation between subsidence patterns and the lithology, suggesting a strong lithological control over subsidence. In addition, the maximum rate of ground subsidence occurs where agricultural activity relies on groundwater exploitation. The InSAR time series within the observation period is well correlated with changes in the depth of the ground water. These observations indicate that the recent acceleration of subsidence is mainly due to anthropogenic activities rather than tectonic motion.

The identification and measurement of ground deformations in urban areas is of great importance for determining the vulnerable parts of the cities that are prone to geohazards, which is a crucial element of both sustainable urban planning and hazard mitigation. Interferometric synthetic aperture radar (InSAR) time series analysis is a very powerful tool for the operational mapping of ground deformation related to urban subsidence and landslide phenomena. With an analysis spanning almost 25 years of satellite radar observations, we compute an InSAR time series of data from multiple satellites (European Remote Sensing satellites ERS-1 and ERS-2, Envisat, Sentinel-1A, and its twin sensor Sentinel-1B) in order to investigate the spatial extent and rate of ground deformation in the megacity of Istanbul. By combining the various multi-track InSAR datasets (291 images in total) and analysing persistent scatterers (PS-InSAR), we present mean velocity maps of ground surface displacement in selected areas of Istanbul. We identify several sites along the terrestrial and coastal regions of Istanbul that underwent vertical ground subsidence at varying rates, from 5 ± 1.2 mm/yr to 15 ± 2.1 mm/yr. The results reveal that the most distinctive subsidence patterns are associated with both anthropogenic factors and relatively weak lithologies along the Haramirede valley in particular, where the observed subsidence is up to 10 ± 2 mm/yr. We show that subsidence has been occurring along the Ayamama river stream at a rate of up to 10 ± 1.8 mm/yr since 1992, and has also been slowing down over time following the restoration of the river and stream system. We also identify subsidence at a rate of 8 ± 1.2 mm/yr along the coastal region of Istanbul, which we associate with land reclamation, as well as a very localised subsidence at a rate of 15 ± 2.3 mm/yr starting in 2016 around one of the highest skyscrapers of Istanbul, which was built in 2010.

Sea-level rise of the Caspian Sea (CS) during the early Khvalynian (approximately 40–25 ka BP) generated hundreds of giant landslides along the sea’s ancient coastlines in western Kazakhstan, which extended hundreds of kilometers. Although similar landslides have been observed along the present-day coastlines of the CS in the area of a prominent high escarpment, it remains unclear whether some of these ancient landslides are still active and whether the movement is slow or catastrophic, as previously suggested. The present study is the first to show evidence proving that the geomorphic responses to sea-level changes of the CS that were triggered in the Pleistocene are currently active. Using interferometric synthetic aperture radar (InSAR) data, we show that one of these giant landslides occurring along the western shore of the Kara-Bogaz-Gol (KBG) lagoon of the CS presents active transient motion, which makes it the world’s largest active landslide reported thus far. Extending more than 25 km along the eastern coast of the inundated KBG depression in a N–S direction with maximum landward expansion of 5 km from the shoreline to the flat Ustyurt Plateau, this landslide conveys ~ 10 × 10⁹ m³ rocks toward the lagoon at a rate of ~ 2.5 cm/year. This event releases a nearly episodic aseismic moment of 6.0 × 10¹⁰ Nm annually, which is equivalent to the response of an Mw 5.1 earthquake. We analyze the present-day evolution of this giant coastal landslide at high temporal and spatial resolutions using Sentinel-1 radar images acquired on descending and ascending modes every 12 days between 2014 and 2020. Modelling with elastic dislocations suggests that the KBG landslide was accommodated mostly by a shallow basal décollement with a nearly horizontal listric slip plane. Moreover, our analysis reveals week-long accelerating slip events at changing amplitudes that occur seasonally with slow, lateral spreading rather than sudden catastrophic motion. A strong correlation between the episodic slip events and seasonal water-level changes in the KBG lagoon suggests a causative mechanism for the transient accelerating slip events. Although water-level changes are widely acknowledged to trigger transient motion on a land mass, such movement, which is similar to a silent earthquake, has not been observed thus far at this mega scale; on an extremely low-angle detachment planes at < 5° with modulation by sea-level changes. This study suggests that present-day sea-level changes can reactivate giant landslides that originated 40–25 ka.

The Himalayan state of Sikkim is prone to some of the world’s largest landslides, which have caused catastrophic damage to lives, properties, and infrastructures in the region. The settlements along the steep valley sides are particularly subject to frequent rainfall-triggered landslide events during the monsoon season. The region has also experienced smaller rock slope failures (RSF) after the 2011 Sikkim earthquake. The surface displacement field is a critical observable for determining landslide depth and constraining failure mechanisms to develop effective mitigation techniques that minimise landslide damage. In the present study, the persistent scatterers InSAR (PSI) method is employed to process the series of Sentinel 1-A/B synthetic aperture radar (SAR) images acquired between 2015 and 2021 along ascending and descending orbits for the selected areas in Gangtok, Sikkim, to detect potentially active, landslide-prone areas. InSAR-derived ground surface displacements and their spatio-temporal evolutions are combined with field investigations to better understand the state of activity and landslide risk assessment. Field investigations confirm the ongoing ground surface displacements revealed by the InSAR results. Some urban areas have been completely abandoned due to the structural damage to residential housing, schools, and office buildings caused by displacement. This paper relates the geotechnical investigations carried out on the ground to the data obtained through interferometric synthetic aperture radar (InSAR), focusing on the triggering mechanisms. A strong correlation between seasonal rainfall and landslide acceleration, as well as predisposing geological-structural setting, suggest a causative mechanism of the landslides.