Similarity reasoning for local surface analysis and recognition

This thesis addresses the similarity assessment of digital shapes, contributing to the analysis of surface characteristics that are independent of the global shape but are crucial to identify a model as belonging to the same manufacture, the same origin/culture or the same typology (color, common decorations, common feature elements, compatible style elements, etc.). To face this problem, the interpretation of the local surface properties is crucial. We go beyond the retrieval of models or surface patches in a collection of models, facing the recognition of geometric patterns across digital models with different overall shape. To address this challenging problem, the use of both engineered and learning-based descriptions are investigated, building one of the first contributions towards the localization and identification of geometric patterns on digital surfaces. Finally, the recognition of patterns adds a further perspective in the exploration of (large) 3D data collections, especially in the cultural heritage domain. Our work contributes to the definition of methods able to locally characterize the geometric and colorimetric surface decorations. Moreover, we showcase our benchmarking activity carried out in recent years on the identification of geometric features and the retrieval of digital models completely characterized by geometric or colorimetric patterns

Contact of a Finger on Rigid Surfaces and Textiles: Friction Coefficient and Induced Vibrations

The tactile information about object surfaces is obtained through perceived contact stresses and frictioninduced vibrations generated by the relative motion between the fingertip and the touched object. The friction forces affect the skin stress-state distribution during surface scanning, while the sliding contact generates vibrations that propagate in the finger skin activating the receptors (mechanoreceptors) and allowing the brain to identify objects and perceive information about their properties. In this article, the friction coefficient between a real human finger and both rigid surfaces and fabrics is retrieved as a function of the contact parameters (load and scanning speed). Then, the analysis of the vibration spectra is carried out to investigate the features of the induced vibrations, measured on the fingernail, as a function of surface textures and contact parameters. While the friction coefficient measurements on rigid surfaces agree with empirical laws found in literature, the behaviour of the friction coefficient when touching a fabric is more complex, and is mainly the function of the textile constructional properties. Results show that frequency spectrum distribution, when touching a rigid surface, is mainly determined by the relative geometry of the two contact surfaces and by the contact parameters. On the contrary, when scanning a fabric, the structure and the deformation of the textile itself largely affect the spectrum of the induced vibration. Finally, some major features of the measured vibrations (frequency distribution and amplitude) are found to be representative of tactile perception compared to psychophysical and neurophysiologic works in literature

Automatic identification of sites prone to topographic seismic amplification effects by the current seismic codes

Current seismic codes provide proxies to estimate seismic amplification effects expected in correspondence of some morphological features. To make possible any empirical validation of these proxies, these features must be univocally identified on the basis of an automatic procedure. To this purpose, based on geomorphological considerations, a GIS-based numerical approach has been developed. The results of a morphometric analysis allowed the correct identification and mapping of the landforms of concern, at a detail corresponding to the resolution of the available digital elevation model (DEM). Some case-studies are provided to show the feasibility of the proposed approach. © 2023 The Author

Spatial patterns of landslide dimension: A tool for magnitude mapping

AbstractThe magnitude of mass movements, which may be expressed by their dimension in terms of area or volume, is an important component of intensity together with velocity. In the case of slow-moving deep-seated landslides, the expected magnitude is the prevalent parameter for defining intensity when assessed as a spatially distributed variable in a given area. In particular, the frequency–volume statistics of past landslides may be used to understand and predict the magnitude of new landslides and reactivations. In this paper we study the spatial properties of volume frequency distributions in the Arno river basin (Central Italy, about 9100km2). The overall landslide inventory taken into account (around 27,500 events) shows a power-law scaling of volumes for values greater than a cutoff value of about 2×104m3. We explore the variability of the power-law exponent in the geographic space by setting up local subsets of the inventory based on neighbourhoods with radii between 5 and 50km. We found that the power-law exponent α varies according to geographic position and that the exponent itself can be treated as a random space variable with autocorrelation properties both at local and regional scale. We use this finding to devise a simple method to map the magnitude frequency distribution in space and to create maps of exceeding probability of landslide volume for risk analysis. We also study the causes of spatial variation of α by analysing the dependence of power-law properties on geological and geomorphological factors, and we find that structural settings and valley density exert a strong influence on mass movement dimensions

Mass movement processes in the Southwest Portuguese Continental Margin during the Late Pleistocene-Holocene : a multidisciplinary approach for volume quantification, estimation of recurrence times and hazard implications

The Alentejo Margin, in the Southwest Portuguese Continental Margin, is a very complex and dynamic geomorphological area, located near the Eurasia-Africa plate boundary and affected by the flow path of the Mediterranean Outflow Water (MOW). This margin comprises the Sines Contourite Drift (SCD), which is the most prominent depositional feature (~2311 km2, 303.9 km perimeter, 98 km length and 35 km width), emplaced in the continental slope of this margin, evolving in four main phases by the action of MOW, since the Late Pleistocene. The interaction between along-slope and downslope processes forms a mixed morphosedimentary setting, which is greatly affected by mass movement activity in the middle and lower continental slopes, during the Late Pleistocene-Holocene. This work analyses the occurrence of mass movement processes in the southwest Portuguese margin, in a total extent of ~85 km×82 km and identifies the main triggering and conditioning factors promoting slope instability during the Late Pleistocene-Holocene and assesses the morphosedimentary evolution of the Sines Contourite Drift. This study was performed through geophysical, sedimentological, physical, geochemical, and geotechnical analyses, using multibeam bathymetry, multichannel seismic and sub-bottom profiler, and gravity cores data. The Alentejo margin is an unstable area, where the presence of a contourite drift significantly contributes for slope instability in consequence of its sediment mechanical properties. The SCD hosts a cluster of dominantly small landslide scars, affecting both steep and smooth slopes. This scar concentration is mainly provided by local intrinsic conditions that favour slope instability in the area. Scars predominantly occur on slope angles steeper than 5º, however sediment properties, especially low consolidation, very low permeability, high pore-pressure, high compressibility and low shear strength greatly promote slope instability in the Alentejo Margin. The inherent instability conditions of the area are increased by frequent seismicity that promotes additional stress, leading to increased slope instability

Geotechnical and hydrological characterization of hillslope deposits for regional landslide prediction modeling

We attempt a characterization of the geotechnical and hydrological properties of hillslope deposits, with the final aim of providing reliable data to distributed catchment-scale numerical models for shallow landslide initiation. The analysis is based on a dataset built up by means of both field tests and laboratory experiments over 100 sites across Tuscany (Italy). The first specific goal is to determine the ranges of variation of the geotechnical and hydrological parameters that control shallow landslide-triggering mechanisms for the main soil classes. The parameters determined in the deposits are: grain size distribution, Atterberg limits, porosity, unit weight, in situ saturated hydraulic conductivity and shear strength parameters. In addition, mineral phases recognition via X-ray powder diffraction has been performed on the different soil types. The deposits mainly consist of well-sorted silty sands with low plastic behavior and extremely variable gravel and clay contents. Statistical analyses carried on these geotechnical and hydrological parameters highlighted that it is not possible to define a typical range of values only with relation to the main mapped lithologies, because soil characteristics are not simply dependent on the bedrock type from which the deposits originated. A second goal is to explore the relationship between soil type (in terms of grain size distribution) and selected morphometric parameters (slope angle, profile curvature, planar curvature and peak distance). The results show that the highest correlation between soil grain size classes and morphometric attributes is with slope curvature, both profile and planar