This work combines very detailed measurements from terrestrial laser scanner (TLS), ground-based interferometry radar (GB-SAR) and ground-penetrating radar (GPR) to diagnose current conditions and to analyse the recent evolution of the Monte Perdido Glacier in the Spanish Pyrenees from 2011 to 2017. Thus, this is currently one of the best monitored small glacier (<0.5 km ² ) worldwide. The evolution of the glacier surface was surveyed with a TLS evidencing an important decline of 6.1 ± 0.3 m on average, with ice losses mainly concentrated over 3 years (2012, 2015 and 2017). Ice loss is unevenly distributed throughout the study period, with 10–15 m thinning in some areas while unchanged areas in others. GB-SAR revealed that areas with higher ice losses are those that are currently with no or very low ice motion. In contrast, sectors located beneath the areas with less ice loss are those that still exhibit noticeable ice movement (average 2–4.5 cm d ^─1 in summer, and annual movement of 9.98 ma ^─1 from ablation stakes data). GPR informed that ice thickness was generally <30 m, though locally 30–50 m. Glacier thinning is still accelerating and will lead to extinction of the glacier over the next 50 years.

Herein, we present results obtained from time-lapse imagery acquired by a digital single-lens reflex camera during 2014–18 used to monitor the Planpincieux Glacier on the Italian side of the Grandes Jorasses (Mont Blanc massif). We processed the images using image cross-correlation to measure the surface kinematics of the most active lobe of the glacier that presents a high velocity and frequent ice detachments. During the monitoring, we observed two or three periods of sharp acceleration per year that culminated with large break-offs followed by analogous decelerations. Overall, we registered more than 350 failures with a volume >100 m³, of which, 14 events had volumes larger than 10 000 m³. The study identified a monotonic positive relationship between the velocity and failure volume that may be used to estimate the volume of the collapses before an event. We identified the thresholds of velocity and acceleration that characterise the activation of the speed-up periods. The study allowed the characterisation of three different instability processes that lead to the break-off of ice chunks from the glacier terminus: (i) disaggregation, (ii) slab fracture and (iii) water tunnelling failure which can be differentiated based on the rheology, the volume involved and the trigger process.

The kinematic acceleration of rock glaciers observed in recent decades shows that the behavior of these landforms is related to climate change. Velocity variations on yearly to seasonal time scales are frequently investigated, but velocity changes measured on shorter time scales (i.e., on hourly resolutions) are as yet poorly investigated. We used a ground based synthetic aperture radar to investigate, on an hourly time scale, the displacement of a rock glacier located in Val Senales (European Alps, northern Italy). We observed velocity fluctuations occurring at a very regular pace, characterized by phases of sharp acceleration (up to 0.9 mm/hr) lasting 4–11 hr followed by long phases of stagnation lasting 13–20 hr. This study describes an unprecedented observation of an hourly velocity rhythm of an active rock glacier and opens up new perspectives in the analysis and interpretation of rock glacier kinematics.

In the Ferret Valley (NW Italy), anthropic activities coexist close to the Grandes Jorasses massif’s glaciological complex. In the past, break-off events have caused damage to people and infrastructure. These events concerned two specific sectors: the Montitaz Lobe (Planpincieux Glacier) and the Whymper Serac (Grandes Jorasses Glacier). Since 2010, permanent and discontinuous survey campaigns have been conducted to identify potential failure precursors, investigate the glacier instability processes, and explore different monitoring approaches. Most of the existing terrestrial apparatuses that measure the surface kinematics have been adopted in the Grandes Jorasses area. The monitoring sites in this specific area are characterized by severe weather, complex geometry, logistic difficulties, and rapid processes dynamics. Such exceptional conditions highlighted the limitations and potentialities of the adopted monitoring approaches, including robotic total station (RTS), GNSS receivers, digital image correlation applied to time-lapse imagery, and terrestrial radar interferometry (TRI). We examined the measurement uncertainty of each system and their monitoring performances. We discussed their principal limitations and possible use for warning purposes. In the Grandes Jorasses area, the use of a time-lapse camera appeared to be a versatile and cost-effective solution, which, however is not suitable for warning applications, as it does not guarantee data continuity. RTS and GNSS have warning potentialities, but the target installation and maintenance in remote environments remain challenging. TRI is the most effective monitoring system for early warning purposes in such harsh conditions, as it provides near-real-time measurements. However, radar equipment is very costly and requires extreme logistic effort. In this framework, we present data integration strategies to overcome the abovementioned limits and we demonstrate that these strategies are optimal solutions to obtain data continuity and robustness.

Digital image correlation (DIC) is a commonly-adopted technique in geoscience and natural hazard studies to measure the surface deformation of various geophysical phenomena. In the last decades, several different correlation functions have been developed. Additionally, some authors have proposed applying DIC to other image representations, such as image gradients or orientation. Many works have shown the reliability of specific methods, but they have been rarely compared. In particular, a formal analysis of the impact of different sources of noise is missing. Using synthetic images, we analysed 15 different combinations of correlation functions and image representations and we investigated their performances with respect to the presence of 13 noise sources. Besides, we evaluated the influence of the size of the correlation template. We conducted the analysis also on terrestrial photographs of the Planpincieux Glacier (Italy) and Sentinel 2B images of the Bodélé Depression (Chad). We observed that frequency-based methods are in general less robust against noise, in particular against blurring and speckling, and they tend to underestimate the displacement value. Zero-mean normalised cross-correlation applied to image intensity showed high-quality results. However, it suffers variations of the shadow pattern. Finally, we developed an original similarity function (DOT) that proved to be quite resistant to every noise source.