Rapid slope instabilities (i.e., rockfalls) involving highway networks in mountainous areas pose a threat to facilities, settlements and life, thus representing a challenge for asset management plans. To identify different morphological expressions of degradation processes that lead to rock mass destabilization, we combined satellite and uncrewed aircraft system (UAS)-based products over two study sites along the State Highway 133 sector near Paonia Reservoir, Colorado (USA). Along with a PS-InSAR analysis covering the 2017–2021 interval, a high-resolution dataset composed of optical, thermal and multi-spectral imagery was systematically acquired during two UAS surveys in September 2021 and June 2022. After a pre-processing step including georeferencing and orthorectification, the final products were processed through object-based multispectral classification and change detection analysis for highlighting moisture or lithological variations and for identifying areas more susceptible to deterioration and detachments at the small and micro-scale. The PS-InSAR analysis, on the other hand, provided multi-temporal information at the catchment scale and assisted in understanding the large-scale morpho-evolution of the displacements. This synergic combination offered a multiscale perspective of the superimposed imprints of denudation and mass-wasting processes occurring on the study site, leading to the detection of evidence and/or early precursors of rock collapses, and effectively supporting asset management maintenance practices.
<p>Along the Adriatic piedmont zone of central-northern Apennines of Italy, the combination of tectonic uplift with Quaternary climate changes caused the alternating phases of fluvial incision and deposition that eventually produced at least four levels of fluvial terraces. Although the fluvial terraces of this sector of the Apennines have been object of many studies since the first half of the twentieth century, their chronology is still object of debate. Consequently, their use as geomorphic markers of landscape evolution can be challenging. The scarcity of geochronological constraints, especially for the older terraced deposits, in addition to the extreme spatial variability of the terrace geomorphological characteristics along adjacent valleys and within different sectors of the same valley, are the main limitations to the utility of fluvial terraces as geomorphic markers of landscape evolution in this sector of the Apennines. This research presents new geomorphological data for the different terrace generations exposed along the southern Marche Apennines between the middle Pleistocene to the late Pleistocene-Holocene, using remote sensing techniques and field investigation, as well as geochronological data from Optically Stimulated Luminescence (OSL) analysis. The fluvial terrace staircase along the Tesino River valley has been selected for the excellent exposure of the different terrace generations along the valley sides, the good accessibility for sampling, and the geomorphological characteristics of the river valley that can be representative of the ones draining the central-northern Adriatic piedmont zone. Findings from this research are useful for enhancing the knowledge on the evolution of the central-northern portion of the Apennines, providing new constraints for unravelling the contributions of tectonics and climate on the late Quaternary evolution of river valleys in the mid-latitudes zone of the Northern hemisphere.</p>
<p>Landslide inventory maps represent a preliminary step toward landslide susceptibility, hazard, and risk assessment. The increasing enhancement of A-DInSAR (Advanced Differential Synthetic Aperture Radar Interferometry) techniques facilitates the detection of Earth&#8217;s surface displacements over large or remote areas. Moreover, applying post-processing tools to the measurements retrieved by PS-InSAR analyses (i.e., one of the most common multitemporal A-DinSAR techniques) permits the representation of gravity-driven processes evolution in both spatial and temporal terms. Nevertheless, geometric distortions linked to the orbit and acquisition parameters of the SAR sensors, along with insufficient site coverage and spatial density of the PS-InSAR analyses, may lead to a lack of information, especially in mountainous areas. To address this problem, we processed the data using different InSAR tool packages and exploited the combination of orbital geometries for different satellites at the regional and local scales. These analyses were applied over an area encompassing four regions in the Central Apennines (Italy), within the framework of a broader national project which aims at mapping and updating landslide-prone slopes interacting with urban centers. For each processed dataset, we compared the spatial coverage and the accuracy of the displacements, providing statistical correlation tests to establish the relationship between the different InSAR tool packages. Therefore, we were able to verify the possible underestimation of the velocity and coherency measurements, and then select the best dataset (or the best combination) for further analyses. Based on the comparison between the dataset and through a semi-automatic approach, we then selected several areas that exceeded specific velocity thresholds and were densely covered by PS. In these areas, classified with a high priority level, detailed analyses were performed through a set of post-processing plugins designed for the software QGIS. Spatial and temporal deformation trends of the PSI results, along with subtle surface patterns within the landslide area, were highlighted by the post-processing analyses. Thus, we derived a detailed geomorphological characterization for the high priority phenomena interacting with cities and infrastructures. While at the regional scale findings from our work help the validation and integration of multi-satellite datasets, at the local scale the proposed workflow can also support the prioritization of site-specific monitoring and intervention planning.</p>
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