Geometric data understanding : deriving case specific features

There exists a tradition using precise geometric modeling, where uncertainties in data can be considered noise. Another tradition relies on statistical nature of vast quantity of data, where geometric regularity is intrinsic to data and statistical models usually grasp this level only indirectly. This work focuses on point cloud data of natural resources and the silhouette recognition from video input as two real world examples of problems having geometric content which is intangible at the raw data presentation. This content could be discovered and modeled to some degree by such machine learning (ML) approaches like deep learning, but either a direct coverage of geometry in samples or addition of special geometry invariant layer is necessary. Geometric content is central when there is a need for direct observations of spatial variables, or one needs to gain a mapping to a geometrically consistent data representation, where e.g. outliers or noise can be easily discerned. In this thesis we consider transformation of original input data to a geometric feature space in two example problems. The first example is curvature of surfaces, which has met renewed interest since the introduction of ubiquitous point cloud data and the maturation of the discrete differential geometry. Curvature spectra can characterize a spatial sample rather well, and provide useful features for ML purposes. The second example involves projective methods used to video stereo-signal analysis in swimming analytics. The aim is to find meaningful local geometric representations for feature generation, which also facilitate additional analysis based on geometric understanding of the model. The features are associated directly to some geometric quantity, and this makes it easier to express the geometric constraints in a natural way, as shown in the thesis. Also, the visualization and further feature generation is much easier. Third, the approach provides sound baseline methods to more traditional ML approaches, e.g. neural network methods. Fourth, most of the ML methods can utilize the geometric features presented in this work as additional features.Geometriassa käytetään perinteisesti tarkkoja malleja, jolloin datassa esiintyvät epätarkkuudet edustavat melua. Toisessa perinteessä nojataan suuren datamäärän tilastolliseen luonteeseen, jolloin geometrinen säännönmukaisuus on datan sisäsyntyinen ominaisuus, joka hahmotetaan tilastollisilla malleilla ainoastaan epäsuorasti. Tämä työ keskittyy kahteen esimerkkiin: luonnonvaroja kuvaaviin pistepilviin ja videohahmontunnistukseen. Nämä ovat todellisia ongelmia, joissa geometrinen sisältö on tavoittamattomissa raakadatan tasolla. Tämä sisältö voitaisiin jossain määrin löytää ja mallintaa koneoppimisen keinoin, esim. syväoppimisen avulla, mutta joko geometria pitää kattaa suoraan näytteistämällä tai tarvitaan neuronien lisäkerros geometrisia invariansseja varten. Geometrinen sisältö on keskeinen, kun tarvitaan suoraa avaruudellisten suureiden havainnointia, tai kun tarvitaan kuvaus geometrisesti yhtenäiseen dataesitykseen, jossa poikkeavat näytteet tai melu voidaan helposti erottaa. Tässä työssä tarkastellaan datan muuntamista geometriseen piirreavaruuteen kahden esimerkkiohjelman suhteen. Ensimmäinen esimerkki on pintakaarevuus, joka on uudelleen virinneen kiinnostuksen kohde kaikkialle saatavissa olevan datan ja diskreetin geometrian kypsymisen takia. Kaarevuusspektrit voivat luonnehtia avaruudellista kohdetta melko hyvin ja tarjota koneoppimisessa hyödyllisiä piirteitä. Toinen esimerkki koskee projektiivisia menetelmiä käytettäessä stereovideosignaalia uinnin analytiikkaan. Tavoite on löytää merkityksellisiä paikallisen geometrian esityksiä, jotka samalla mahdollistavat muun geometrian ymmärrykseen perustuvan analyysin. Piirteet liittyvät suoraan johonkin geometriseen suureeseen, ja tämä helpottaa luonnollisella tavalla geometristen rajoitteiden käsittelyä, kuten väitöstyössä osoitetaan. Myös visualisointi ja lisäpiirteiden luonti muuttuu helpommaksi. Kolmanneksi, lähestymistapa suo selkeän vertailumenetelmän perinteisemmille koneoppimisen lähestymistavoille, esim. hermoverkkomenetelmille. Neljänneksi, useimmat koneoppimismenetelmät voivat hyödyntää tässä työssä esitettyjä geometrisia piirteitä lisäämällä ne muiden piirteiden joukkoon

Imaging and discrete modelling of sand shape

The shape of particles is known to play an important role in soil behaviour, with significant effects of engineering responses. Investigating how the shape of particles can be measured and quantified is therefore considered increasingly important in modern soil mechanics. This is propelled by the advent of computer based image-analyses and discrete modelling algorithms, which have opened new ways to tackle this problem. This work demonstrates how these two techniques can be made to work together. Image analyses are performed on x-rays micro-tomographs (µ-CT) of triaxial sand specimens, focusing on the characterisation and quantification of particle shapes. Two with very different particle shape sands are studied in details: Caicos ooids (rounded) and Hostun sand (angular). A discrete Digital Volume Correlation (DVC) algorithm is then used to track the kinematics of individual grains (around 50000 for each sand specimen) during the triaxial test and measure, with good precision, their cumulated displacements and rotations. Joint analysis of the shape and kinematic databases acquired is performed to find how particle shape descriptors are related to observed kinematics at the microscale level. It appears that true sphericity is a good predictor of upper bound rotational restraint. Modelling is based on the Discrete Element Method (DEM). Models that introduce rolling resistance at the contact are widely employed in DEM simulations, these approaches offer substantial computational benefits at the prize of increased calibration complexity. In this work, the values of true sphericity obtained by image analysis of the grains, either directly by 3D acquisition or by correlation with simpler to obtain 2D shape measures, are used to establish mechanically equivalent rotational restrictions. An empirical relation between a contact parameter (rolling friction) and a 3D grain shape descriptor (true sphericity is first calibrated - using both specimen-scale and grain scale results from two triaxial tests in Hostun sand and Caicos ooids. It is then validated by simulating other triaxial tests (1) with the same sands, but in different conditions (2) with Ottawa sand, for which 3D grain images were also available for examination, and (3) with Ticino sand, for which only 2D grain images were available. Finally, results of large-scale DEM simulations on the Cone Penetration Test (CPT) - exploiting the new proposed contact model - are presented. Experimental data on the CPT performed in a Calibration Chamber (CC) comprised of Ticino sand are successfully fitted by the numerical penetration curves at different confining pressures and conditions. A parametric study about the influence of particle shape and particle shape variability put in evidence the strong-coupled effects of rolling and frictional resistances at the particles contacts. The work described in this thesis will ease the use of DEM for large-scale simulations of geotechnical engineering problems.Se sabe que la forma de las partículas juega un papel importante en el comportamiento del suelo, con efectos significativos de las respuestas mecánicas relevantes en ingeniería geotécnica. Por lo tanto, investigar cómo se puede medir y cuantificar la forma de las partículas se considera cada vez más importante en la mecánica del suelo moderna. Esto se acrecienta debido a las técnicas de análisis computacionales de imágenes y algoritmos de modelado discreto (DEM), que han abierto nuevas formas de abordar este problema. Este trabajo demuestra cómo se pueden hacer que estas dos técnicas funcionen juntas. Los análisis de imagen se realizan sobre micro-tomografías de rayos X (µ-CT) de muestras de arena en celdas triaxiales, centrándose en la caracterización y cuantificación de la forma de las partículas. Se estudian en detalle dos arenas con la forma de sus partículas muy diferentes: Caicos ooids (redondeados) y Hostun sand (angular). Luego se utiliza un algoritmo discreto de correlación de volumen digital (DVC) para rastrear la cinemática de granos individuales (alrededor de 50000 por cada muestra de arena) durante la prueba triaxial y medir, con buena precisión, sus desplazamientos y rotaciones acumulados. El análisis conjunto de la forma y las bases de datos cinemáticas adquiridas se realiza para encontrar cómo los descriptores de forma de partículas se relacionan con la cinemática observada a nivel de micro-escala. Resulta que la esfericidad verdadera predice bien el límite superior de rotación de una partícula. La modelización numérica se basa en el Método de Elementos Discretos (DEM). Los modelos que introducen resistencia a la rotación en el contacto se emplean ampliamente en simulaciones DEM, estos enfoques ofrecen beneficios computacionales sustanciales a costa de una mayor complejidad de calibración. En este trabajo, los valores de esfericidad verdadera (i.e., true sphericity) obtenidos mediante análisis de imagen de los granos, ya sea directamente por adquisición 3D o por correlación con medidas de forma 2D más simples, se utilizan para establecer restricciones de rotación mecánicamente equivalentes. Una relación empírica entre un parámetro de contacto (rolling friction) y un descriptor de forma de grano 3D (la esfericidad verdadera) se calibra primero, utilizando los resultados de la escala de muestras y de la escala de granos de dos pruebas triaxiales en las arenas de Hostun y de Caicos. Luego se valida simulando otras pruebas triaxiales (1) con las mismas arenas, pero en diferentes condiciones (2) con arena de Ottawa, para la que también estaban disponibles imágenes 3D de granos para su examen, y (3) con arena de Ticino, para la cual solo estaban disponibles imágenes 2D de los granos. Finalmente, se presentan resultados de simulaciones DEM a gran escala de la prueba de penetración de cono (CPT), aprovechando el nuevo modelo de contacto propuesto. Los datos experimentales del CPT realizado en una cámara de calibración (CC) sobre arena de Ticino se ajustan con éxito por las curvas de penetración numérica a diferentes presiones y condiciones de confinamiento. Un estudio paramétrico sobre la influencia de la forma de las partículas y la variabilidad de las formas de las partículas puso de manifiesto los efectos fuertemente acoplados de las resistencias rotacional y friccional en los contactos entre partículas. El trabajo descrito en esta tesis facilitará el uso de DEM para simulaciones a gran escala en problemas de ingeniería geotécnica.Postprint (published version

Distinct Element Method Applied on Old Masonry Structures

Masonry structures have specific aspects and different numerical approaches are available or studying their behavior. The analysis of masonry constructions is a complex task Lourenco, 2002), especially under special loads and when the soil-structure interaction becomes essential for studying the real behavior

Computing fast search heuristics for physics-based mobile robot motion planning

Mobile robots are increasingly being employed to assist responders in search and rescue missions. Robots have to navigate in dangerous areas such as collapsed buildings and hazardous sites, which can be inaccessible to humans. Tele-operating the robots can be stressing for the human operators, which are also overloaded with mission tasks and coordination overhead, so it is important to provide the robot with some degree of autonomy, to lighten up the task for the human operator and also to ensure robot safety. Moving robots around requires reasoning, including interpretation of the environment, spatial reasoning, planning of actions (motion), and execution. This is particularly challenging when the environment is unstructured, and the terrain is \textit{harsh}, i.e. not flat and cluttered with obstacles. Approaches reducing the problem to a 2D path planning problem fall short, and many of those who reason about the problem in 3D don't do it in a complete and exhaustive manner. The approach proposed in this thesis is to use rigid body simulation to obtain a more truthful model of the reality, i.e. of the interaction between the robot and the environment. Such a simulation obeys the laws of physics, takes into account the geometry of the environment, the geometry of the robot, and any dynamic constraints that may be in place. The physics-based motion planning approach by itself is also highly intractable due to the computational load required to perform state propagation combined with the exponential blowup of planning; additionally, there are more technical limitations that disallow us to use things such as state sampling or state steering, which are known to be effective in solving the problem in simpler domains. The proposed solution to this problem is to compute heuristics that can bias the search towards the goal, so as to quickly converge towards the solution. With such a model, the search space is a rich space, which can only contain states which are physically reachable by the robot, and also tells us enough information about the safety of the robot itself. The overall result is that by using this framework the robot engineer has a simpler job of encoding the \textit{domain knowledge} which now consists only of providing the robot geometric model plus any constraints

Imbibition in Disordered Media

The physics of liquids in porous media gives rise to many interesting phenomena, including imbibition where a viscous fluid displaces a less viscous one. Here we discuss the theoretical and experimental progress made in recent years in this field. The emphasis is on an interfacial description, akin to the focus of a statistical physics approach. Coarse-grained equations of motion have been recently presented in the literature. These contain terms that take into account the pertinent features of imbibition: non-locality and the quenched noise that arises from the random environment, fluctuations of the fluid flow and capillary forces. The theoretical progress has highlighted the presence of intrinsic length-scales that invalidate scale invariance often assumed to be present in kinetic roughening processes such as that of a two-phase boundary in liquid penetration. Another important fact is that the macroscopic fluid flow, the kinetic roughening properties, and the effective noise in the problem are all coupled. Many possible deviations from simple scaling behaviour exist, and we outline the experimental evidence. Finally, prospects for further work, both theoretical and experimental, are discussed.Comment: Review article, to appear in Advances in Physics, 53 pages LaTe

Spatial prediction of landslide susceptibility/intensity through advanced statistical approaches implementation: applications to the Cinque Terre (Eastern Liguria, Italy)

Landslides are frequently responsible for considerable huge economic losses and casualties in mountainous regions especially nowadays as development expands into unstable hillslope areas under the pressures of increasing population size and urbanization (Di Martire et al. 2012). People are not the only vulnerable targets of landslides. Indeed, mass movements can easily lay waste to everything in their path, threatening human properties, infrastructures and natural environments. Italy is severely affected by landslide phenomena and it is one of the most European countries affected by this kind of phenomena. In this framework, Italy is particularly concerned with forecasting landslide effects (Calcaterra et al. 2003b), in compliance with the National Law n. 267/98, enforced after the devastating landslide event of Sarno (Campania, Southern Italy). According to the latest Superior Institute for the Environmental Protection and Research (ISPRA, 2018) report on "hydrogeological instability" of 2018, it emerges that the population exposed to landslides risk is more than 5 million and in particular almost half-million falls into very high hazard zones. The slope stability can be compromised by both natural and human-caused changes in the environment. The main reasons can be summarised into heavy rainfalls, earthquakes, rapid snow-melts, slope cut due to erosions, and variation in groundwater levels for the natural cases whilst slopes steepening through construction, quarrying, building of houses, and farming along the foot of mountainous zone correspond to the human component. This Ph.D. thesis was carried out in the Liguria region, inside the Cinque Terre National Park. This area was chosen due to its abundance of different types of landslides and its geological, geomorphological and urban characteristics. The Cinque Terre area can be considered as one of the most representative examples of human-modified landscape. Starting from the early centuries of the Middle Ages, local farmers have almost completely modified the original slope topography through the construction of dry-stone walls, creating an outstanding terraced coastal landscape (Terranova 1984, 1989; Terranova et al. 2006; Brandolini 2017). This territory is extremely dynamic since it is characterized by a complex geological and geomorphological setting, where many surficial geomorphic processes coexist, along with peculiar weather conditions (Cevasco et al. 2015). For this reason, part of this research focused on analyzing the disaster that hit the Cinque Terre on October, 25th, 2011. Multiple landslides took place in this occasion, triggering almost simultaneously hundreds of shallow landslides in the time-lapse of 5-6 hours, causing 13 victims, and severe structural and economic damage (Cevasco et al. 2012; D\u2019Amato Avanzi et al. 2013). Moreover, this artificial landscape experienced important land-use changes over the last century (Cevasco et al. 2014; Brandolini 2017), mostly related to the abandonment of agricultural activity. It is known that terraced landscapes, when no longer properly maintained, become more prone to erosion processes and mass movements (Lesschen et al. 2008; Brandolini et al. 2018a; Moreno-de-las-Heras et al. 2019; Seeger et al. 2019). Within the context of slope instability, the international community has been focusing for the last decade on recognising the landslide susceptibility/hazard of a given area of interest. Landslide susceptibility predicts "where" landslides are likely to occur, whereas, landslide hazard evaluates future spatial and temporal mass movement occurrence (Guzzetti et al., 1999). Although both definitions are incorrectly used as interchangeable. Such a recognition phase becomes crucial for land use planning activities aimed at the protection of people and infrastructures. In fact, only with proper risk assessment governments, regional institutions, and municipalities can prepare the appropriate countermeasures at different scales. Thus, landslide susceptibility is the keystone of a long chain of procedures that are actively implemented to manage landslide risk at all levels, especially in vulnerable areas such as Liguria. The methods implemented in this dissertation have the overall objective of evaluating advanced algorithms for modeling landslide susceptibility. The thesis has been structured in six chapters. The first chapter introduces and motivates the work conducted in the three years of the project by including information about the research objectives. The second chapter gives the basic concepts related to landslides, definition, classification and causes, landslide inventory, along with the derived products: susceptibility, hazard and risk zoning, with particular attention to the evaluation of landslide susceptibility. The objective of the third chapter is to define the different methodologies, algorithms and procedures applied during the research activity. The fourth chapter deals with the geographical, geological and geomorphological features of the study area. The fifth chapter provides information about the results of the applied methodologies to the study area: Machine Learning algorithms, runout method and Bayesian approach. Furthermore, critical discussions on the outcomes obtained are also described. The sixth chapter deals with the discussions and the conclusions of this research, critically analysing the role of such work in the general panorama of the scientific community and illustrating the possible future perspectives

Modelling the surface energetics of patchy arctic tundra snowcover

A combination of field observations and measurements were used to study the energy-balance of a patchy arctic tundra snow-cover during the winter of 2003/2004 at a mountain tundra site in Northern Sweden. To quantify the effect of patchy snow-cover on surface energetic, the Met. Office Surface Exchange Scheme (MOSES 2) was employed to simulate surface snow dynamics. Surface snow patchiness was controlled by the interaction of blowing snow with surface topography and vegetation, with deep drifts forming in topographic hollows and tall shrub beds. Some exposed ridge tops remained exposed for the majority of the winter. The surface patchiness was found to significantly alter the surface energetics, and the interaction between snow and snow-free surfaces was critical to accurately numerically simulating snow-cover ablation. The assumption of uniform snow- covers in large-scale atmospheric models may lead to significant errors in model simulations. It was found that for large-scale models, heterogeneous snow-covers can be adequately represented by the use of separate energy-balances for snow and snow-free surfaces respectively with a single underlying soil layer. The proportions of each surface can be represented using a snow covered fraction which is a parameterisation of the distribution of snow depths. Simulated surface fluxes, particularly surface runoff and heat and water vapour, were found to be highly sensitive to the exact form of this parameterisation. No field evidence was found for the advection of turbulent energy between snow and snow-free surface

DART: A 3D Model for Remote Sensing Images and Radiative Budget of Earth Surfaces

Modeling the radiative behavior and the energy budget of land surfaces is relevant for many scientific domains such as the study of vegetation functioning with remotely acquired information. DART model (Discrete Anisotropic Radiative Transfer) is developed since 1992. It is one of the most complete 3D models in this domain. It simulates radiative transfer (R.T.) in the optical domain: 3D radiative budget and remote sensing images (i.e., radiance, reflectance, brightness temperature) of vegetation and urban Earth surfaces, for any atmosphere, wavelength, sun/view direction, altitude and spatial resolution. It uses an innovative multispectral approach (flux tracing, exact kernel, discrete ordinate techniques) over the whole optical domain. Here, its potential is illustrated with the case of urban and tropical forest canopies. Moreover, three recent improvements in terms of functionality and operability are presented: account of Earth/Atmosphere curvature for oblique remote sensing measurements, importation of 3D objects simulated as the juxtaposition of triangles with the possibility to transform them into 3D turbid objects, and R.T. simulation in landscapes that have a continuous topography and landscapes that are non repetitive. Finally, preliminary results concerning two application domains are presented. 1) 2D distribution of the reflectance, brightness temperature and radiance measured by a geostationary satellite over a whole continent. 2) 3D radiative budget of natural and urban surfaces with a DART energy budget (EB) component that is being developed. This new model, called DARTEB, is intended to simulate the energy budget of land surfaces

Research on Soil Erosion

Soil loss for erosion is a natural phenomenon in soil dynamics, influenced by climate, soil intrinsic properties, and morphology, that can both trigger and enhance the process. Anthropic activities, like inappropriate agricultural practices, deforestation, overgrazing, forest fires and construction activities, may exert a remarkable impact on erosion processes or, on the other hand, contribute to soil erosion mitigation through a sustainable management of natural resources. The book is the continuation of previously published "Soil Erosion Studies"; it is organized in a unique section collecting nine chapters focusing on a variety of aspects of the erosion phenomena

Analysis of the precipitation characteristics on the Tibetan Plateau using Remote Sensing, Ground-Based Instruments and Cloud models

In this Thesis work, carried out in the frame of CEOP-AEGIS, an EU FP7 funded project, the problem of the precipitation monitoring over the Tibetan Plateau has been addressed. Despite the Plateau key role in water cycle of South East Asia (and in the life of 1.5 billions of people), there is a critical lack of knowledge, because the current estimates of relevant geophysical parameters are based on sparse and scarce observations than can not provide the required accuracy for quantitative studies and reliable monitoring, especially on a climate change perspective. This is particularly true for precipitation, the geophysical parameter with highest spatial and temporal variability. The constantly increasing availability of Earth system observation from spaceborne sensors makes the remote sensing an effective option for precipitation monitoring and the main focus of the present work is the implementation and applications for three years of data (2008, 2009 and 2010) of an array of satellite precipitation techniques, based on different methodological approaches and data sources. First, a sensitivity study on the capability of the most used satellite sensors to detect precipitation at the ground, assessed with respect to raingauges data for selected case studies, has been carried out. Then, two physically based techniques have been implemented based on satelliteborne active (for snow-rate) and passive (for rain-rate) microwave sensor data and the output used for calibrate geostationary IR-based techniques. Finally, two well established global multisensor precipitation products have been considered for reference and intercomparison. All the techniques have been implemented for the 3 years and the results compared at different spatial and temporal scales. The analysis of daily rain amount has shown that in general global algorithms are able to estimate rain amount larger than the ones estimated by other techniques during the monsoon season. In cold months global techniques underestimate precipitation amount and areas, resulting in a dry bias with respect to IR calibrated techniques. Case studies compared with ground radar precipitation data on convective episodes shown that global products tend to underestimate precipitation areas, while IR calibrated techniques provides reliable rainrate patterns, as compared with radar data. Unfortunately, the number of radar case studies was not large enough to allow significant validation studies, and also non data were available for cold months. Annual precipitation cumulated maps show marked differences among the techniques: IR calibrated techniques generally overestimate precipitation amount by a factor of 2 with respect of global products. Reasons for discrepancies are investigated and discussed, pointing out the uncertainties that will probably be solved only with the exploitation of new satellite missions