Evaluation of snow depth retrievals from ICESat-2 using airborne laser-scanning data

The unprecedented precision of the altimetry satellite ICESat-2 and the increasing availability of high-resolution elevation datasets open new opportunities to measure snow depth in mountains, a critical variable for ecosystems and water resources monitoring. We retrieved snow depth over the upper Tuolumne basin (California, USA) for three years by differencing ICESat-2 ATL06 snow-on elevations and various snow-off elevation sources, including ATL06 and external digital elevation models. Snow depth derived from ATL06 data only (snow-on and snow-off) provided a poor temporal and spatial coverage, limiting its utility. However, using airborne lidar or satellite photogrammetry elevation models as snow-off elevation source yielded an accuracy of ~0.2 m (bias), a precision of ~0.5 m for low slopes and ~1.2 m for steeper areas, compared to eight reference airborne lidar snow depth maps. The snow depth derived from ICESat-2 ATL06 will help address the challenge of measuring the snow depth in unmonitored mountainous areas.</p

Multi-platform, Multi-scale and Multi-temporal 4D Glacier Monitoring. The Rutor Glacier Case Study

At present most alpine glaciers are not in equilibrium with the current climate, as a result they are undergoing a dramatic mass loss. Monitoring glacial variations is crucial to assess the consequences of climate change on the territory. In this work different geomatics techniques are exploited to measure and monitor the Rutor glacier over the years. In this study two different techniques were adopted to generate 3 digital surface models (DSMs): aerial and satellite photogrammetry. Two photogrammetric aerial surveys were carried out: at the end of the hydrological year 2019/20 and at the end of the following hydrological year. Additionally, a very high-resolution satellite stereo pair, acquired by the Pléiades-1A platform in 2017, was processed to assess whether satellite images can be applied to extract the 3D surface of the Rutor glacier. In order to evaluate the Rutor glacier mass-balance throughout the years several reference points were positioned and measured before the 2021 aerial flight. Thanks to the presence of the materialized points the 2021 model is considered as the ‘Reference Model’ against which subsequent models can be compared for glacier analysis. This model was validated by means of a comparison with the authoritative Regional DSM based on LiDAR surveys. In alpine glaciers, the positioning of artificial square cross target in time invariant areas is crucial to enable a multitemporal 4D analysis. The use of very high-resolution satellite imagery allows large areas to be mapped in 3D, but with lower accuracies proportionally decreasing with respect to slope and exposure

The 2015 landslide and tsunami in Taan Fiord, Alaska

Glacial retreat in recent decades has exposed unstable slopes and allowed deep water to extend beneath some of those slopes. Slope failure at the terminus of Tyndall Glacier on 17 October 2015 sent 180 million tons of rock into Taan Fiord, Alaska. The resulting tsunami reached elevations as high as 193 m, one of the highest tsunami runups ever documented worldwide. Precursory deformation began decades before failure, and the event left a distinct sedimentary record, showing that geologic evidence can help understand past occurrences of similar events, and might provide forewarning. The event was detected within hours through automated seismological techniques, which also estimated the mass and direction of the slide - all of which were later confirmed by remote sensing. Our field observations provide a benchmark for modeling landslide and tsunami hazards. Inverse and forward modeling can provide the framework of a detailed understanding of the geologic and hazards implications of similar events. Our results call attention to an indirect effect of climate change that is increasing the frequency and magnitude of natural hazards near glaciated mountains

RESCUE MANAGEMENT AND ASSESSMENT OF STRUCTURAL DAMAGE BY UAV IN POST-SEISMIC EMERGENCY

Abstract. The increasing frequency of emergencies urges the need for a detailed and thorough knowledge of the landscape. The first hours after a disaster are not only chaotic and problematic, but also decisive to successfully save lives and reduce damage to the building stock. One of the most important factors in any emergency response is to get an adequate awareness of the real situation, what is only possible after a thorough analysis of all the available information obtained through the Italian protocol Topography Applied to Rescue. To this purpose geomatic tools are perfectly suited to create, manage and dynamically enrich an organized archive of data to have a quick and functional access to information useful for several types of analysis, helping to develop solutions to manage the emergency and improving the success of rescue operations. Moreover, during an emergency like an earthquake, the conventional inspection to assess the damage status of buildings requires special tools and a lot of time. Therefore, given the large number of buildings requiring safety measures and rehabilitation, efficient use of limited resources such as time and equipment, as well as the safety of the involved personnel are important aspects. The applications shown in the paper are intended to underline how the above-mentioned objective, in particular the rehabilitation interventions of the built heritage, can be achieved through the use of data acquired from UAV platform integrated with geographic data stored in GIS platforms

Gradual caldera collapse at Bárdarbunga volcano, Iceland, regulated by lateral magma outflow

Large volcanic eruptions on Earth commonly occur with a collapse of the roof of a crustal magma reservoir, forming a caldera. Only a few such collapses occur per century, and the lack of detailed observations has obscured insight into the mechanical interplay between collapse and eruption.We usemultiparameter geophysical and geochemical data to show that the 110-squarekilometer and 65-meter-deep collapse of Bárdarbunga caldera in 2014-2015 was initiated through withdrawal of magma, and lateral migration through a 48-kilometers-long dike, from a 12-kilometers deep reservoir. Interaction between the pressure exerted by the subsiding reservoir roof and the physical properties of the subsurface flow path explain the gradual, nearexponential decline of both collapse rate and the intensity of the 180-day-long eruption.</p

Incorporating Season and Solar Specificity into Renderings made by a NeRF Architecture using Satellite Images

As a result of Shadow NeRF and Sat-NeRF, it is possible to take the solar angle into account in a NeRF-based framework for rendering a scene from a novel viewpoint using satellite images for training. Our work extends those contributions and shows how one can make the renderings season-specific. Our main challenge was creating a Neural Radiance Field (NeRF) that could render seasonal features independently of viewing angle and solar angle while still being able to render shadows. We teach our network to render seasonal features by introducing one more input variable -- time of the year. However, the small training datasets typical of satellite imagery can introduce ambiguities in cases where shadows are present in the same location for every image of a particular season. We add additional terms to the loss function to discourage the network from using seasonal features for accounting for shadows. We show the performance of our network on eight Areas of Interest containing images captured by the Maxar WorldView-3 satellite. This evaluation includes tests measuring the ability of our framework to accurately render novel views, generate height maps, predict shadows, and specify seasonal features independently from shadows. Our ablation studies justify the choices made for network design parameters.Comment: 18 pages, 17 figures, 10 table