An investigation into the dynamical and statistical properties of dominant ocean surface waves using close-range remote sensing

Denne avhandlingen er basert på forskningsresultat som behandler statistiske og dynamiske egenskaper av dominante vinddrevne overflatebølger i åpent hav. Med uttrykket dominante bølger refererer vi her til de største bølgene, med størst energi, i en gitt sjøtilstand. Bølgedrevne prosesser er viktige både i klimasammenheng via atmosfære--hav interaksjon som drives i stor grad av bølgebrytning, samt for kommersiell og rekreasjonell offshorevirksomhet p.g.a. risikoen for å bli utsatt for f.eks. ekstreme enkeltbølger. Både bølgebrytning og ekstrembølgestatistikk er i skrivende stund ufullstendig representert i teoretiske og numeriske modeller. Arbeidet som presenteres i denne avhandlingen undersøker de ovennevnte temaene ved bruk av bølgeobservasjoner som er primært samlet inn på Ekofiskfeltet i den sentrale delen av Nordsjøen. Observasjonsdatasettene består av en langtidstidsserie av laser-altimetermålinger og stereoskopiske videodata fra Ekofisk, samt videomålinger av brytende bølger fra et forskningstokt i nordre Stillehavet. Forskningsresultatene er presentert i artikkelform med to publiserte verk og ett innlevert manuskript. Det blir påvist en tydelig forbindelse mellom økt bølgebrytning og dominante bølgegrupper, et resultat som tidligere har blitt påvist i laboratorie- og modelleksperiment, men sjeldent ved bruk av feltobservasjoner. Tredimensjonale stereo-rekonstruksjoner viser også at ekstreme bølgekammer, både brytende og ikke-brytende, følger nylig utviklet teori om ikke-lineær bølgegruppedynamikk. Dette funnet har konsekvenser f.eks. for estimering av geometriske og kinematiske bølgeegenskaper såsom steilhet og kamhastighet fra endimensjonale tidsseriemålinger. Som følge av en langtidsanalyse av endimensjonal bølgestatistikk blir det vist at enrettet, langkammet og bratt sjø mest sannsynlig leder til ekstreme enkeltbølger med statistiske egenskaper som avviker systematisk fra ordinære statistiske modeller. Tredimensjonal, kortsiktig tid-rom-statistikk av ekstreme bølgekammer blir også undersøkt v.h.a. stereomålingene fra Ekofisk. Her blir det vist at statistiske modeller utvidet fra endimensjonale til tredimensjonale bølgefelt i snitt er velegnet til å beskrive forekomsten av de høyeste bølgekammene, spesielt for relativt store tid-rom segment.The research presented in this thesis characterizes statistical and dynamical aspects of dominant wind-generated surface gravity waves inferred from field observations in intermediate-to-deep water. Dominant waves are the most energetic waves in a sea state, and as such, understanding their behavior is important in both engineering and geophysical contexts. Large waves impart considerable impact forces on marine structures such as oil and gas platforms and offshore wind turbines, and these forces may multiply manyfold when waves break. Wave breaking in deep water, often referred to as whitecapping, is also a key, though incompletely understood, process regulating the transfer of momentum, gas and heat across the air-sea interface, and must thus be accurately parameterized in large-scale weather and climate models. Current theory holds that the wave breaking process is closely linked kinematically and dynamically to the group structure inherent in ocean surface wave fields. Wave group dynamics is also believed to govern the characteristic shape and motion of so-called extreme or rogue waves, whose correct statistical description is central to many offshore activities. The work presented herein shows, using state-of-the-art stereoscopic imaging techniques employed at the Ekofisk platform complex in the central North Sea, that large-scale wave breaking activity in the open ocean is strongly enhanced in dominant wave groups. The topic of wave group-modulated wave breaking has received considerable attention in the past two decades from theoretical, numerical and laboratory perspectives; however, quantitative field studies of the phenomenon remain comparatively rare. The current results also support the general notion that the dominant waves in a given sea state regulate the breaking of shorter waves. The statistics of extreme wave crest elevations is investigated using a novel long-term laser altimeter data set, also located at the Ekofisk field. The validity of the extreme values is verified using a newly developed despiking methodology, and the quality controlled data set, which covers storm events over an 18-year period, is used to investigate the effects of wave steepness and directionality on crest height statistics. Narrow directional spread combined with high wave steepness is found to lead to crest height statistics that deviate the most from standard linear and second-order formulations. Finally, geometric wave shape and crest speed dynamics are analyzed for the highest wave crests encountered in three-dimensional, spatially and temporally resolved segments of the stereo-reconstructed sea surface fields. The directly measured crest steepness is found to conform to the classical breaking limit of Stokes, whereas crest steepness estimated from one-dimensional time series measurements using the linear gravity-wave dispersion relation are systematically higher. This may be at least in part explained by the observation that the directly measured crest speed just before, during and after the moment of maximum crest elevation slows down compared to the linear gravity-wave phase speed estimate. For the first time, the crest speed slowdown is shown with field measurements to apply to both breaking and non-breaking dominant wave crests.Doktorgradsavhandlin

On the Groupiness and Intermittency of Oceanic Whitecaps

The enhancement of wave breaking activity during wave group passage is investigated using coherent field observations of the instantaneous sea surface elevation and whitecap coverage from platform-based stereo video measurements in the central North Sea. Passing wave groups are shown to be associated with a two to threefold enhancement in the probability distribution of total whitecap coverage W whereas the enhancement of active whitecap coverage WA is approximately fivefold. Breaking time scales and intermittency characteristics are also investigated with the inclusion of a secondary data set of W and WA observations collected during a research cruise in the North Pacific. The time scale analysis suggests a universal periodicity in wave breaking activity within a representative sea-surface area encompassing approximately one dominant wave crest. The breaking periodicity is shown to be closely linked to the peak period of the dominant wave components, suggesting that long-wave modulation of wave breaking is a predominant mechanism controlling the intermittency of wave breaking across scales.publishedVersio

Adaptive Methods for Point Cloud and Mesh Processing

Point clouds and 3D meshes are widely used in numerous applications ranging from games to virtual reality to autonomous vehicles. This dissertation proposes several approaches for noise removal and calibration of noisy point cloud data and 3D mesh sharpening methods. Order statistic filters have been proven to be very successful in image processing and other domains as well. Different variations of order statistics filters originally proposed for image processing are extended to point cloud filtering in this dissertation. A brand-new adaptive vector median is proposed in this dissertation for removing noise and outliers from noisy point cloud data. The major contributions of this research lie in four aspects: 1) Four order statistic algorithms are extended, and one adaptive filtering method is proposed for the noisy point cloud with improved results such as preserving significant features. These methods are applied to standard models as well as synthetic models, and real scenes, 2) A hardware acceleration of the proposed method using Microsoft parallel pattern library for filtering point clouds is implemented using multicore processors, 3) A new method for aerial LIDAR data filtering is proposed. The objective is to develop a method to enable automatic extraction of ground points from aerial LIDAR data with minimal human intervention, and 4) A novel method for mesh color sharpening using the discrete Laplace-Beltrami operator is proposed. Median and order statistics-based filters are widely used in signal processing and image processing because they can easily remove outlier noise and preserve important features. This dissertation demonstrates a wide range of results with median filter, vector median filter, fuzzy vector median filter, adaptive mean, adaptive median, and adaptive vector median filter on point cloud data. The experiments show that large-scale noise is removed while preserving important features of the point cloud with reasonable computation time. Quantitative criteria (e.g., complexity, Hausdorff distance, and the root mean squared error (RMSE)), as well as qualitative criteria (e.g., the perceived visual quality of the processed point cloud), are employed to assess the performance of the filters in various cases corrupted by different noisy models. The adaptive vector median is further optimized for denoising or ground filtering aerial LIDAR data point cloud. The adaptive vector median is also accelerated on multi-core CPUs using Microsoft Parallel Patterns Library. In addition, this dissertation presents a new method for mesh color sharpening using the discrete Laplace-Beltrami operator, which is an approximation of second order derivatives on irregular 3D meshes. The one-ring neighborhood is utilized to compute the Laplace-Beltrami operator. The color for each vertex is updated by adding the Laplace-Beltrami operator of the vertex color weighted by a factor to its original value. Different discretizations of the Laplace-Beltrami operator have been proposed for geometrical processing of 3D meshes. This work utilizes several discretizations of the Laplace-Beltrami operator for sharpening 3D mesh colors and compares their performance. Experimental results demonstrated the effectiveness of the proposed algorithms

Assessment of Paleo-Landscape Features using Advanced Remote Sensing Techniques, Modelling and GIS Methods in the Lake Manyara Basin, Northern Tanzania

In researching the evolution of hominids, the East African Rift System acts as a vital region. The rift valleys enabled some of the most sensational hominid findings to date. Various hypotheses have been developed in the last decades, which try to explain the influence of changes in paleo-climate, paleo-landscape and paleo-environment on hominin evolution in the Quaternary. Additionally, the sediments and the morphology of the East African Rift System provide excellent terrestrial archives for paleo-environmental reconstruction. Lake Manyara is located in an endorheic basin in the eastern arm of the East African Rift System in northern Tanzania. The surroundings of the Lake Manyara are in the focus of paleontological and archaeological investigations. For instance, two hominin bearing sites were found within the catchment of the Makuyuni River, as well as artefacts and fossils are periodically uncovered. The study area, which is located east of the present-day lake, provides an insight into relevant geological and geomorphological drivers of paleo-landscape evolution of the whole region. This thesis aims at contributing to the understanding of landscape evolution in the Lake Manyara region. Compared to other regions in the East African rift system, few landscape evolution studies took place for the Lake Manyara basin. As such, an integrative scientific investigation of the spatial situation of paleo-landscape features and of paleo-lake level fluctuations is missing. The proposed study utilizes state-of-the-art remote sensing based research methods in evaluating the landscape, and in concluding from present-day landforms and processes, how the landscape developed during the Pleistocene and Holocene. In striving to accomplish this goal, this cumulative dissertation comprises eight central research questions, which are introduced in a conceptual framework. The research questions have been considered in seven scientific publications, which describe the applied methodologies and results in detail. The framework of the thesis provides a coherent and detailed interpretation and discussion of the scientific findings. The research questions and outcomes of the analyses are listed below. Key drivers of landscape development in the East African Rift System are tectonic and tectonically induced processes. Drainage network, stream longitudinal profiles and basin analysis based on topographic analyses, as well as lineaments extracted from remote sensing images, were successfully used as methods in identifying tectonic activity and related features in rift areas. The application of a gully erosion model suggests that the gully channel systems in the study area are relatively stable and that they had developed prior to the last significant lake regression. The paleo-landscape and the paleo-environment are closely connected to lake level changes of the paleo-Lake Manyara. Hence, a key question concerns the extent of the Manyara Beds, which are lacustrine deposits that indicate the maximum extent of the paleo-Lake Manyara. A combined analysis, utilizing ASTER multispectral indices and topographic parameters from a digital elevation model, led to the spatial delineation of lacustrine sediments. Their extent indicates a relation to lacustrine sediments in the southern part of the basin, and reveals lacustrine / palustrine deposits further east. A methodological comparison of Support Vector Machines and Boosted Regression Trees, which served as classification methods to identify the lacustrine sediments, exhibited high accuracies for both approaches, with minor advantages for Support Vector Machines. Closely related to the previous research question is the question on the spatial distribution of surface substrates. By incorporating a WorldView-2 scene and Synthetic Aperture Radar data to the previously mentioned datasets, it was possible to distinguish between nine topsoil and lithological target classes in the study area. The surface substrates indicate the underlying lithologies, sediments and soils, as well as soil formation processes. Between the village of Makuyuni and the present-day Lake Manyara, paleo-shorelines and terraces were formed by various paleo-lake levels. Questions arise, at which elevation these features occur and what is the maximum elevation, which was reached. ALOS PALSAR and TerraSAR-X backscatter intensity information provided the possibility of an area-wide mapping of those morphological features. Some radiometric dates exist for stromatolites from a distinct paleo-shoreline level, which support the interpretation of the lake fluctuations. The paleo-shoreline, which was identified with the highest elevation, coincides with the elevation of the lowest possible outlet of the closed Manyara basin. It can be assumed that the paleo-Lake Manyara over-spilled into the neighboring Engaruka and Natron-Magadi basins. The question of the location of sites with a high probability of artefact and/or fossil presence is important for future archaeological and paleontological research. ASTER remote sensing data and topographic indices contributed likewise to the predictive modelling of probabilities of archaeological and paleontological sites in the study area. Generally, paleontological sites are found on a higher elevation, compared to Stone Age sites. In addition, fossil sites seem to be related to stable paleo-landscape features according to this study’s findings. The results of this dissertation provide new insights in the landscape development of the Lake Manyara basin. The scientific findings contribute to the understanding of the landscape evolution for the study area, as well as for the neighboring basins in the East African Rift System. The applied geospatial methodologies can be transferred to other study areas with similar research needs

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

Reconstruction tridimensionnelle de scènes sous- marines à partir de séquences d'images acquises par des caméras acoustiques

According to recent studies, climate change is having a significant impact on our marine environment inducing temperature increases, chemistry changes, ocean circulation influencing both population dynamics and underwater structure stability. Environmental change is thus a growing scientific concern requiring a regular monitoring of the evolution of underwater ecosystems with appropriate studies combined with accurate and relevant detailed information extraction and preservation. Tracking and modeling such changes in a marine environment is one of the current challenges for underwater exploration. The most common technique used to observe underwater environment, relies on vision-based systems either acoustical or optical. Optical cameras are widely used for acquiring images of the seafloor/underwater structures as they can provide information about the physical properties of the image that will enable the description of the observed scene (color, reflection, geometry). However, the range limitation and non-ideal underwater conditions (dark and turbid waters) make acoustic imaging the most reliable means of sight inside the underwater environment. Traditional sonar systems cannot provide an acoustic image sequences like optical cameras. To overcome those drawbacks, acoustic camera was built. They can produce real time high resolution underwater image sequences, with high refresh rate. Moreover, compared to optical devices, they can acquire acoustic images in turbid, deep and dark water making acoustic camera imaging a reliable means for observing underwater environment. However, although acoustic cameras can provide 2-D resolution of the order of centimeters, they do not resolve the altitude of observed scene. Thus they offer a 2D environment representation which provides incomplete information about the underwater environment. Hence, it would be very interesting to have a system which can provide height information as well as a high resolution. This is the purpose of this thesis where we developed a methodology that enables 3D reconstruction of underwater scenes using sequences of acoustic images. The proposed methodology is inspired from stereovision techniques that allow 3D information computation from image sequences. It consists of two main steps. In the first step, we propose an approach that enables the extraction of relevant salient points from several images. In the second step, two different methods have been proposed (curvilinear approach and volumetric approach) in order to reconstruct the observed scene using images acquired from different viewpoints. The Covariance Matrix Adaptation Evolution Strategy algorithm (CMA-ES) has been used to compute camera movement between images. This movement has been then used to retrieve 3D information. The methodology performances have been evaluated: feature extraction approach has been assessed using criteria of good detection, repeatability and good localization and 3D reconstruction approach has been assessed by comparison between estimated camera movement and 3D information with real data.Depuis que les études des impacts des changements climatiques ont montré que le milieu marin pourrait être énormément fragilisé par la disparition de certaines espèces de sa faune et de sa flore, ainsi que par le vieillissement rapide de son infrastructure sous-marine, la recherche de systèmes d'observation robustes et continus est classée parmi les sujets de recherche les plus prioritaires des scientifiques. Généralement, l'observation de l'environnement et l'inspection des infrastructures sous-marines se font au moyen des capteurs imageurs tels que les capteurs optiques ou les systèmes acoustiques. Toutefois, ces outils souffrent de certaines limitations lors de leur utilisation. Les caméras optiques fournissent des données caractérisées par une bonne résolution permettant une interprétation facile des scènes observées mais aussi par des problèmes techniques lors de l'acquisition liés aux conditions du milieu marin (e.g. manque de visibilité) empêchant une observation continue du milieu. Les sonars traditionnels produisent aussi des images mais ils n'offrent pas de séquences d'images de haute cadence tels que les capteurs optiques, et leur utilisation est parfois contrainte dans les milieux portuaires et de faible profondeur. C'est pour pallier ces problèmes que les caméras acoustiques ont été conçues. Elles ont la capacité d'acquérir des séquences d'images multi-vues avec une haute cadence et de fonctionner dans des milieux très turbides. Néanmoins, ces caméras ne produisent que des images en 2D où l'élévation de la scène observée est inconnue. Or, une représentation 2D de l'environnement ne peut présenter qu'une partie des informations, elle n'est pas en mesure de représenter "fidèlement" le milieu où le phénomène est observé. Ceci n'est possible qu'à travers une représentation 3D. L'objectif de cette thèse est donc de développer une approche de reconstruction 3D de scènes sous-marines à partir de séquences d'images acquises par des caméras acoustiques. Pour ce faire, nous nous sommes inspirés du principe de la stéréovision pour une reconstruction 3D à partir de points saillants. Néanmoins, la géométrie et la nature bruitée des images acoustiques ne permettent pas une application directe du principe de la stéréovision. Ainsi nous proposons dans cette thèse, une méthodologie de reconstruction 3D qui répond aux problématiques posées par les images des caméras acoustiques. Elle se base, en première partie, sur la conception d'un processus d'extraction de points saillants pertinents sur lesquels, en deuxième partie, va pouvoir s'appuyer la reconstruction 3D de la scène observée. Pour la reconstruction 3D, nous proposons deux approches différentes : une approche curviligne et une approche volumique. Dans ces deux approches, l'algorithme d'optimisation CMA-ES issu de la famille des stratégies d'évolution intervient dans le calcul du mouvement de la caméra entre les images, la détermination de ce mouvement permettant par la suite, l'estimation des informations 3D. La performance de l'approche d'extraction de primitives ainsi que celle des approches de reconstruction 3D ont été évaluées: la première au travers de critères de bonne détection, de répétabilité et de bonne localisation et la deuxième au travers de la comparaison du mouvement et des informations 3D estimés avec des données réelles