The technological heart of the study is Multi-Temporal Interferometric Synthetic Aperture Radar, or MT-InSAR, a technique that has transformed how scientists monitor ground deformation. Synthetic aperture radar satellites bounce microwave signals off the Earth’s surface and record the phase of the returning waves. When the same point on the ground is imaged repeatedly over months or years, tiny changes in the distance between the satellite and the surface shift the phase of the reflected signal. By comparing these phase differences across many acquisitions, researchers can measure ground movement with millimetre-level precision, without ever setting foot on the unstable slope. The Cyprus team processed both ascending and descending orbit datasets, meaning the satellite flew over the study area from different directions, which allowed them to sample the movement of the ground along two distinct lines of sight and to build a more complete picture of the three-dimensional deformation field.

The researchers applied this technique to landslides already catalogued in an existing inventory of southwestern Cyprus, covering slopes classified as active, dormant and relict. This classification matters because it reflects the state of a landslide at the time of mapping: active landslides are currently moving, dormant ones have not moved recently but retain the potential to reactivate, and relict ones are ancient features formed under different climatic conditions that are generally considered stable. The team extracted the Line-of-Sight, or LOS, velocities for each landslide from the radar data and then asked whether the measured rates differed systematically between these activity classes. The answer was emphatic. The largest LOS velocities were observed in landslides characterised as active, followed by dormant and then relict landslides, a hierarchy that confirms the radar measurements are capturing genuine differences in slope behaviour rather than noise.

That validation is more important than it might sound. One of the persistent challenges in landslide science is that inventories are often compiled from aerial photographs, historical records and field visits, all of which involve a degree of subjective judgement. If satellite-derived velocities align cleanly with independently assigned activity classes, it suggests both datasets are reliable and, more intriguingly, that radar could in future be used to update and refine inventories automatically. For a country like Cyprus, where development continues to push onto marginal slopes, an objective, repeatable measure of which landslides are truly moving could directly inform planning decisions and early-warning strategies. The study effectively demonstrates that the velocity signal from space carries real diagnostic information about the state of a landslide.

The second major strand of the analysis asked which materials move fastest, and here the geology of Cyprus provides a striking answer. The largest displacement rates corresponded mostly to outcrops of fine-grained clastic rocks, including marls, radiolarian mudstones and mélange. These rock types share a critical property: weak shear strength. Marls, which are mixtures of clay and calcium carbonate, are notorious in engineering geology because they swell when wetted, slake when dried and lose strength dramatically as pore water pressure rises. Radiolarian mudstones and the chaotic, mixed rock assemblages known as mélange behave similarly, deforming readily under stress. When such weak materials sit on a slope, the resistance to sliding is low, and once movement begins, the ground can creep steadily for years. The radar data confirmed that these lithologies host the fastest-moving terrain in the study area, tying the observed deformation directly to the mechanical properties of the bedrock.

To move beyond simple correlations, the team turned to a machine-learning interpretability tool called Shapley Additive Explanations, or SHAP. Borrowed from cooperative game theory, SHAP analysis quantifies how much each input variable contributes to a model’s prediction for any individual case, distributing credit among factors in a way that is mathematically consistent. In the context of this study, the method allowed the researchers to rank the influence of geological, geomorphological, environmental and geotechnical factors on the measured LOS velocities. The headline finding was unambiguous: rainfall emerged as the primary factor influencing the increase in LOS velocity. In other words, while many ingredients conspire to create a landslide, precipitation is the dominant throttle controlling how quickly the ground moves once instability is established.

This result carries a profound implication for how landslide hazard should be understood and managed. The geological and geotechnical characteristics of a site determine whether a landslide can occur at all; they set the stage by providing weak materials, favourable orientations and susceptible slope geometries. But once a landslide has been initiated, the tempo of its movement is governed largely by the water delivered from above. Rainfall infiltrates the slope, raises pore water pressures within the sliding mass, reduces the effective stress that holds the material together and lubricates the failure surface. The Cyprus findings suggest that monitoring rainfall and incorporating precipitation records into deformation forecasts could substantially improve predictions of when slow-moving slides will accelerate, which is precisely the information that engineers and emergency managers need most.

Among the geotechnical indices examined, two stood out. The Plasticity Index, or PI, a standard measure of how much water a soil can absorb before it transitions between consistency states, generally exhibited a positive correlation with ground velocity. High-PI clays are more compressible, more prone to swelling and shrinkage, and more sensitive to moisture changes, so it makes intuitive sense that slopes founded on such materials move faster. Conversely, the Geological Strength Index, or GSI, a qualitative scale that characterises the overall strength of a rock mass based on its structure and the condition of its discontinuities, demonstrated a weak negative correlation with velocity. Stronger, more intact rock masses move more slowly, as expected, though the weakness of the correlation suggests that intact rock strength plays a secondary role compared with moisture conditions and the intrinsic weakness of fine-grained units.

The choice of Cyprus as a case study gives the work practical weight well beyond the island. Southwestern Cyprus is underlain by the Mamonia Complex and related units, a tectonically jumbled assemblage of weak sedimentary rocks that has produced some of the island’s most problematic ground. Landslides in this region have damaged roads and infrastructure for decades, and the Geological Survey Department of Cyprus, whose scientists provided the geological and geotechnical data underpinning the study, maintains detailed records of the affected areas. The research was funded through the European Union’s Horizon 2020 programme under a Marie Skłodowska-Curie grant, reflecting the European dimension of the problem: weak, clay-bearing formations and intensifying rainfall extremes threaten slopes across the entire Mediterranean basin, from Italy and Greece to Turkey and North Africa.

What makes the study resonate beyond its regional focus is the methodological template it offers. By fusing freely available satellite radar data with conventional geological mapping and laboratory-derived geotechnical indices, and by interrogating the relationships with a modern interpretability framework, the researchers have shown how the pieces of the landslide puzzle can be assembled quantitatively rather than anecdotally. The approach requires no expensive ground instrumentation, can be repeated as new satellite acquisitions arrive, and scales naturally from a single slope to an entire country. As climate change intensifies rainfall variability across the Mediterranean and elsewhere, the ability to identify which slopes are moving, how fast, and what drives their acceleration will become an essential tool for protecting communities. The Cyprus study suggests that the answer, at least for the fastest-moving hazards, may literally be falling from the sky.

Subject of Research: Statistical correlation of InSAR-derived landslide ground movement rates with activity class and geological, geotechnical and climatic causal factors in southwestern Cyprus

Article Title: Correlating InSAR-derived ground movement rates with landslide activity class and causal factors: a case study from Cyprus

Article References: Tzampoglou, P., Loukidis, D., Tolomei, C., & Svigkas, N. (2026). Correlating InSAR-derived ground movement rates with landslide activity class and causal factors: a case study from Cyprus. Scientific Reports. https://doi.org/10.1038/s41598-026-74387-6

Image Credits: AI Generated

DOI: 10.1038/s41598-026-74387-6

Keywords: InSAR, landslides, Cyprus, MT-InSAR, rainfall, SHAP analysis, geotechnical indices, Plasticity Index, Geological Strength Index, marls, remote sensing, natural hazards

The team, led by Ankita Ghoke, Priyom Roy and colleagues, combined three complementary lines of evidence to track the slope’s evolution. Eighteen cloud-free optical images from Indian Resourcesat-2 and 2A satellites, the European Sentinel-2 mission and the high-resolution Cartosat-3 sensor allowed them to map morphological changes between 2013 and 2025. They then applied multi-temporal interferometric synthetic aperture radar, or MT-InSAR, using the Small Baseline Subset technique on Sentinel-1 radar data to measure millimeter-scale ground deformation over four distinct time windows. Finally, field campaigns after the 2024 reactivation documented the structural and geological weaknesses that make the slope so prone to failure. Together, these datasets reveal a landslide that is not a single event but a slow-motion, retrogressive collapse that keeps climbing uphill and swallowing new ground.

The optical record tells a striking story of escalation. In March 2013, the unstable zone was a modest, elongated feature roughly 500 to 600 meters long. A major reactivation in June 2013, coinciding with the disastrous Kedarnath cloudburst that devastated much of Uttarakhand, stretched the slide to about 965 meters and carved the first prominent head scarp while blocking the Shambhu River. Between 2014 and 2016 the failure continued to retreat upslope, damming and re-damming the river. Around October 2018, an entirely new landslide initiated to the southwest, and by late 2019 its scar had merged with the main slide mass, enlarging the failure zone still further. By 2024, four separate head scarps were visible on the slope, evidence of multi-scarp retrogression still underway. The landslide now covers approximately 0.95 square kilometers, and imagery shows that several settlements in its path were destroyed as it grew.

The radar measurements add a crucial dimension: they show the slope moving before it visibly fails. In the first analysis phase, from October 2014 to October 2016, monitoring points on the flanking slopes recorded average line-of-sight velocities of roughly 40 millimeters per year, with deformation accelerating during the 2015 and 2016 monsoons before complete failure and scarp formation. In the second phase, a point tracking the nascent secondary landslide crept at 13.6 millimeters per year before a rapid acceleration culminating in the October 2018 collapse. Later phases recorded velocities between about 5 and 12 millimeters per year, each acceleration episode closely following periods of intense rainfall. The pattern is classic transient landslide behavior: stability, then primary creep, then accelerating motion, then failure, with monsoon precipitation acting as the trigger on a slope already predisposed to collapse by its geology.

That geology is unfavourable in almost every respect. The slope lies near the Main Central Thrust in the seismically active Lesser Himalaya, underlain by highly sheared talc schist, carbonaceous phyllite, quartzite and slate of the Lameri Formation, all draped in thick, loose colluvium. Fieldwork revealed foliation planes dipping at 45 to 50 degrees, parallel to the slope face, creating ready-made planar failure surfaces. The team also mapped transverse cracks, active groundwater seepage channels exuding along those cracks, and linear discontinuities that appear to be faults or joints. Particularly worrying is the village of Kuwari itself, which sits on a previously stabilized portion of the landslide body that field evidence now shows is bulging and deforming anew. A road constructed across the secondary landslide zone in early 2022 has further destabilized that section, a reminder that human activity can amplify an already fragile situation.

Meanwhile, the lake behind the debris dam keeps growing. The first impoundment formed in June 2013 and drained in 2015; a second formed in November 2016, partially drained in October 2017 and re-formed in 2018. From November 2021 onward the water body expanded relentlessly: roughly 885 meters long by April 2022, about 900 meters by October 2022, 1,050 meters by October 2023, and approximately 1,130 meters long and 100 meters wide by October 2024, the largest extent on record. Each enlargement reflects fresh debris choking the valley and raises the volume of water poised above downstream communities. History offers little comfort: previous research indicates that 80 to 90 percent of landslide-dammed lakes fail within their first year, and the Kuwari dam has already been partially breached by the river cutting a narrow channel through the debris.

To assess how stable that dam actually is, the researchers applied two geomorphic indices. The Morphological Obstruction Index, calculated at 3.82, places the dam in the uncertain evolution domain, while the Hydro-morphological Dam Stability Index, computed from the dam volume, upstream catchment area of about 2.46 square kilometers and channel gradient, falls squarely within the instability domain. The dam itself is a type III barrier in the classification of Costa and Schuster, meaning debris has moved both upstream and downstream of the valley and completely obstructs it. With an estimated height of around 40 meters and a surface area near the crest of roughly 10,000 square meters, the structure is an unconsolidated pile of landslide debris, not engineered material, and it is already being eroded by the river flowing through it.

The most dramatic part of the study is the flood simulation. Using HEC-RAS version 6.7, the team modeled a complete overtopping breach of the dam, drawing breach geometry from an empirical relationship derived from historical dam failures. Assuming the full 3.7 million cubic meter reservoir and a 17-meter breach height, the model predicts an average breach width of 48.3 meters forming in just 0.64 hours, less than forty minutes. The resulting flood would race down the narrow valley at a peak velocity of 15 meters per second near the breach, with overbank flooding extending about six kilometers downstream to Choting village, where water could rise up to 10 meters above normal levels and inundate agricultural terraces. Beyond Choting, the flow would remain channelized but still dangerous, reaching the villages of Melkhet, Deosari and Dewal at average velocities of 6 to 8 meters per second, fast enough to threaten anything along the riverbanks.

The authors are careful to note that the simulation is a predictive, end-member scenario that cannot yet be validated, and that its results carry uncertainties in breach width, formation time, erosion rates and dam material properties. But the broader message is hard to escape. The Kuwari landslide is an active, compound hazard in one of the world’s most landslide-prone countries, which a global analysis by Froude and Petley ranked highest in landslide fatalities. The study’s authors call for continuous monitoring, an early warning system for downstream communities, slope stabilization measures, and strict controls on construction across already scarped slopes. As climate change intensifies monsoon extremes across the Himalaya and infrastructure development pushes further into fragile terrain, the integrated approach demonstrated here, pairing satellite radar with optical imagery, field geology and hydrodynamic modeling, may become an essential template for spotting the next Kuwari before its lake bursts.

Subject of Research: Reactivation dynamics of the Kuwari landslide in Uttarakhand, India, and assessment of landslide lake outburst flood hazard using remote sensing and hydrodynamic modelling.

Article Title: Reactivation dynamics of the Kuwari landslide (Uttarakhand, India) and assessment of LLOF hazard using optical imagery, MT-InSAR and hydrodynamic modelling

Article References: Ghoke, A., Gaur, A., Roy, P., Jalan, P., Martha, T. R., & Das, I. C. (2026). Reactivation dynamics of the Kuwari landslide (Uttarakhand, India) and assessment of LLOF hazard using optical imagery, MT-InSAR and hydrodynamic modelling. Discover Geoscience, 4(1), Article 345. https://doi.org/10.1007/s44288-026-00717-w

Image Credits: AI Generated

DOI: 10.1007/s44288-026-00717-w

Keywords: Kuwari landslide, Uttarakhand, Himalaya, MT-InSAR, landslide-dammed lake, LLOF, HEC-RAS, Sentinel-1, dam breach, natural hazards, remote sensing, monsoon rainfall