A Multivariate Comparison of Drone-Based Structure from Motion and Drone-Based Lidar for Dense Topographic Mapping Applications

Unmanned aircraft systems (UAS), also known as drones, are an increasingly popular method of collecting surveying and mapping data. Two common drone-based mapping techniques are lidar and structure from motion (SfM) photogrammetry, and a frequently-heard (yet nearly impossible to answer) question is: “which is better?” The most common metric for comparison is spatial accuracy, but the two techniques also vary in other key aspects, such as cost, complexity, learning curve, payload requirements, acquisition and processing speeds, and abilities to map under canopy or in vegetation. While there is no “one-size-fits-all” technology or technique, comparisons of drone-based lidar and SfM photogrammetry along all of these different dimensions and various settings can help surveyors and mappers make informed decisions in purchasing and operating UAS-based systems. This study performs these comparisons using data acquired with two remote aircraft at a project site with a robust control network and high-accuracy reference data located in Stevenson, Washington. The results shed light on the relative strengths and weaknesses of UAS-SfM with post processed kinematic (PPK) image georeferencing (UAS-SfM-PPK) and UAS-lidar. The products created using these two techniques typically provide comparable data accuracies with some differences, as a function of terrain, ground cover type and surface texture. Although UAS-SfM-PPK is generally less expensive, imposes less stringent requirements for the remote aircraft, requires less expert knowledge and training, and yields higher data densities, an overarching recommendation from this research is that UAS-SfM-PPK be considered the default, general-purpose technique for many mapping projects. However, there are a number of specific scenarios in which UAS-lidar is preferable to UAS-SfM-PPK, and it is critical to understand these cases. Additionally, while the combination of UAS-SfM-PPK and UAS-lidar would typically be unnecessarily expensive and complex for most projects, the synergistic use of both techniques could provide an optimal solution for the most demanding projects.Author keywords: UAS lidar; UAS SfM; structure from motion; aerial lidar; vertical accuracy assessment; topographic mapping; drones; PP

The Einstein@Home search for radio pulsars and PSR J2007+2722 discovery

Einstein@Home aggregates the computer power of hundreds of thousands of volunteers from 193 countries, to search for new neutron stars using data from electromagnetic and gravitational-wave detectors. This paper presents a detailed description of the search for new radio pulsars using Pulsar ALFA survey data from the Arecibo Observatory. The enormous computing power allows this search to cover a new region of parameter space; it can detect pulsars in binary systems with orbital periods as short as 11 minutes. We also describe the first Einstein@Home discovery, the 40.8 Hz isolated pulsar PSR J2007+2722, and provide a full timing model. PSR J2007+2722\u27s pulse profile is remarkably wide with emission over almost the entire spin period. This neutron star is most likely a disrupted recycled pulsar, about as old as its characteristic spin-down age of 404 Myr. However, there is a small chance that it was born recently, with a low magnetic field. If so, upper limits on the X-ray flux suggest but cannot prove that PSR J2007+2722 is at least ∼100 kyr old. In the future, we expect that the massive computing power provided by volunteers should enable many additional radio pulsar discoveries. © 2013. The American Astronomical Society. All rights reserved

Remote Sensing for Land Administration 2.0

The reprint “Land Administration 2.0” is an extension of the previous reprint “Remote Sensing for Land Administration”, another Special Issue in Remote Sensing. This reprint unpacks the responsible use and integration of emerging remote sensing techniques into the domain of land administration, including land registration, cadastre, land use planning, land valuation, land taxation, and land development. The title was chosen as “Land Administration 2.0” in reference to both this Special Issue being the second volume on the topic “Land Administration” and the next-generation requirements of land administration including demands for 3D, indoor, underground, real-time, high-accuracy, lower-cost, and interoperable land data and information

UAV photogrammetry ground control reductions using GNSS

Ph. D. Thesis.Unmanned aerial vehicles (UAVs) are now well-established as platforms for photogrammetric data acquisition. Their advantages, particularly over conventional manned aerial platforms, relate to their low cost, ease of use, rapid deployability and low-level flying for the collection of centimetre-level spatial resolution imagery. Coupled with recent innovations in photogrammetry and computer vision, UAVs equipped with consumer grade digital cameras are now frequently used to generate centimetre-resolution and accuracy mapping products, such as dense point clouds, digital elevation models and orthomosaics. Despite the efficiency of UAV data acquisition, the continued need for ground control implementation for photogrammetric image orientation remains a substantial workflow constraint. In addition to the associated costs, ground control must be implemented strategically, and usually extensively, to ensure photogrammetric products meet the accuracy requirements of large scale mapping, which may or may not be possible given constraints of the intended application. This research uses high precision, UAV-based GNSS (Global Navigation Satellite System) positioning techniques to substantially reduce ground control requirements by directly determining UAV image positions with centimetre-level accuracy and precision. The Precise Point Positioning (PPP) technique is applied and can yield centimetre-level planimetric and decimetre height accuracy photogrammetric mapping without GCPs, whilst the height accuracy can be improved to the centimetre-level using a single GCP. Unlike the standard relative GNSS positioning technique, PPP alleviates all spatial operating constraints associated with the installation and use of a local ground-based GNSS reference station, or the need to operate within the bounds of a permanent GNSS reference station network. Such a workflow simplifies operational logistics, and enables large-scale photogrammetric mapping from UAVs in even the most remote and challenging geographic locations globally. The approach was tested on 11 fixed wing UAV datasets, acquired at two sites in Northumberland, north-east England, which had varying ground control configurations. UAV flight durations, meaning time between launch and landing, were 12-42 minutes. It is shown that the main limitation of UAV-based PPP application is the inherent possibility of GNSS cycle slips and limited observation spans that inhibit the convergence of float ambiguity estimates. Although PPP camera position estimates were biased in such cases, GCPs were still minimised due to the retained precision of the PPP camera position estimates and constraints on the image block.EPSR

Software for Exascale Computing - SPPEXA 2016-2019

This open access book summarizes the research done and results obtained in the second funding phase of the Priority Program 1648 "Software for Exascale Computing" (SPPEXA) of the German Research Foundation (DFG) presented at the SPPEXA Symposium in Dresden during October 21-23, 2019. In that respect, it both represents a continuation of Vol. 113 in Springer’s series Lecture Notes in Computational Science and Engineering, the corresponding report of SPPEXA’s first funding phase, and provides an overview of SPPEXA’s contributions towards exascale computing in today's sumpercomputer technology. The individual chapters address one or more of the research directions (1) computational algorithms, (2) system software, (3) application software, (4) data management and exploration, (5) programming, and (6) software tools. The book has an interdisciplinary appeal: scholars from computational sub-fields in computer science, mathematics, physics, or engineering will find it of particular interest

Computational methods for high-throughput metabolomics

Hoffmann N. Computational methods for high-throughput metabolomics. Bielefeld: Universität Bielefeld; 2014.The advent of analytical technologies being broadly and routinely applied in biology and biochemistry for the analysis and characterization of small molecules in biological organisms has brought with it the need to process, analyze, compare, and evaluate large amounts of experimental data in a highly automated fashion. The most prominent methods used in these fields are chromatographic methods capable of separating complex mixtures of chemical compounds by properties like size or charge, coupled to mass spectrometry detectors that measure the mass and intensity of a compound's ion or its fragments eluting from the chromatographic separation system. One major problem in these high-throughput applications is the automatic extraction of features quantifying the compounds contained in the measured results and their reliable association among multiple measurements for quantification and statistical analysis. The main goal of this thesis is the creation of scalable and robust methods for highly automated processing of large numbers of samples. Of special importance is the comparison of different samples in order to find similarities and differences in the context of metabolomics, the study of small chemical compounds in biological organisms. We herein describe novel algorithms for retention time alignment of peak and chromatogram data from one- and two-dimensional gas chromatography-mass spectrometry experiments in the application area of metabolomics. We also perform a comprehensive evaluation of each method against other state-of-the-art methods on publicly available datasets with genuine biological backgrounds. In addition to these methods, we also describe the underlying software framework Maltcms and the accompanying graphical user interface Maui, and demonstrate their use on instructive application examples

Reversible Computation: Extending Horizons of Computing

This open access State-of-the-Art Survey presents the main recent scientific outcomes in the area of reversible computation, focusing on those that have emerged during COST Action IC1405 "Reversible Computation - Extending Horizons of Computing", a European research network that operated from May 2015 to April 2019. Reversible computation is a new paradigm that extends the traditional forwards-only mode of computation with the ability to execute in reverse, so that computation can run backwards as easily and naturally as forwards. It aims to deliver novel computing devices and software, and to enhance existing systems by equipping them with reversibility. There are many potential applications of reversible computation, including languages and software tools for reliable and recovery-oriented distributed systems and revolutionary reversible logic gates and circuits, but they can only be realized and have lasting effect if conceptual and firm theoretical foundations are established first

Modélisation tridimensionnelle précise de l'environnement à l’aide des systèmes de photogrammétrie embarqués sur drones

Abstract : Images acquired from unmanned aerial vehicles (UAVs) can provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modeling. Solutions developed for this purpose are mainly operating based on photogrammetry concepts, namely UAV-Photogrammetry Systems (UAV-PS). Such systems are used in applications where both geospatial and visual information of the environment is required. These applications include, but are not limited to, natural resource management such as precision agriculture, military and police-related services such as traffic-law enforcement, precision engineering such as infrastructure inspection, and health services such as epidemic emergency management. UAV-photogrammetry systems can be differentiated based on their spatial characteristics in terms of accuracy and resolution. That is some applications, such as precision engineering, require high-resolution and high-accuracy information of the environment (e.g. 3D modeling with less than one centimeter accuracy and resolution). In other applications, lower levels of accuracy might be sufficient, (e.g. wildlife management needing few decimeters of resolution). However, even in those applications, the specific characteristics of UAV-PSs should be well considered in the steps of both system development and application in order to yield satisfying results. In this regard, this thesis presents a comprehensive review of the applications of unmanned aerial imagery, where the objective was to determine the challenges that remote-sensing applications of UAV systems currently face. This review also allowed recognizing the specific characteristics and requirements of UAV-PSs, which are mostly ignored or not thoroughly assessed in recent studies. Accordingly, the focus of the first part of this thesis is on exploring the methodological and experimental aspects of implementing a UAV-PS. The developed system was extensively evaluated for precise modeling of an open-pit gravel mine and performing volumetric-change measurements. This application was selected for two main reasons. Firstly, this case study provided a challenging environment for 3D modeling, in terms of scale changes, terrain relief variations as well as structure and texture diversities. Secondly, open-pit-mine monitoring demands high levels of accuracy, which justifies our efforts to improve the developed UAV-PS to its maximum capacities. The hardware of the system consisted of an electric-powered helicopter, a high-resolution digital camera, and an inertial navigation system. The software of the system included the in-house programs specifically designed for camera calibration, platform calibration, system integration, onboard data acquisition, flight planning and ground control point (GCP) detection. The detailed features of the system are discussed in the thesis, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The accuracy of the results was evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy were assessed. The second part of this thesis concentrates on improving the techniques of sparse and dense reconstruction. The proposed solutions are alternatives to traditional aerial photogrammetry techniques, properly adapted to specific characteristics of unmanned, low-altitude imagery. Firstly, a method was developed for robust sparse matching and epipolar-geometry estimation. The main achievement of this method was its capacity to handle a very high percentage of outliers (errors among corresponding points) with remarkable computational efficiency (compared to the state-of-the-art techniques). Secondly, a block bundle adjustment (BBA) strategy was proposed based on the integration of intrinsic camera calibration parameters as pseudo-observations to Gauss-Helmert model. The principal advantage of this strategy was controlling the adverse effect of unstable imaging networks and noisy image observations on the accuracy of self-calibration. The sparse implementation of this strategy was also performed, which allowed its application to data sets containing a lot of tie points. Finally, the concepts of intrinsic curves were revisited for dense stereo matching. The proposed technique could achieve a high level of accuracy and efficiency by searching only through a small fraction of the whole disparity search space as well as internally handling occlusions and matching ambiguities. These photogrammetric solutions were extensively tested using synthetic data, close-range images and the images acquired from the gravel-pit mine. Achieving absolute 3D mapping accuracy of 11±7 mm illustrated the success of this system for high-precision modeling of the environment.Résumé : Les images acquises à l’aide d’aéronefs sans pilote (ASP) permettent de produire des données de résolutions spatiales et temporelles uniques pour la modélisation tridimensionnelle (3D). Les solutions développées pour ce secteur d’activité sont principalement basées sur des concepts de photogrammétrie et peuvent être identifiées comme des systèmes photogrammétriques embarqués sur aéronefs sans pilote (SP-ASP). Ils sont utilisés dans plusieurs applications environnementales où l’information géospatiale et visuelle est essentielle. Ces applications incluent notamment la gestion des ressources naturelles (ex. : agriculture de précision), la sécurité publique et militaire (ex. : gestion du trafic), les services d’ingénierie (ex. : inspection de bâtiments) et les services de santé publique (ex. : épidémiologie et gestion des risques). Les SP-ASP peuvent être subdivisés en catégories selon les besoins en termes de précision et de résolution. En effet, dans certains cas, tel qu’en ingénierie, l’information sur l’environnement doit être de haute précision et de haute résolution (ex. : modélisation 3D avec une précision et une résolution inférieure à un centimètre). Pour d’autres applications, tel qu’en gestion de la faune sauvage, des niveaux de précision et de résolution moindres peut être suffisants (ex. : résolution de l’ordre de quelques décimètres). Cependant, même dans ce type d’applications les caractéristiques des SP-ASP devraient être prises en considération dans le développement des systèmes et dans leur utilisation, et ce, pour atteindre les résultats visés. À cet égard, cette thèse présente une revue exhaustive des applications de l’imagerie aérienne acquise par ASP et de déterminer les challenges les plus courants. Cette étude a également permis d’établir les caractéristiques et exigences spécifiques des SP-ASP qui sont généralement ignorées ou partiellement discutées dans les études récentes. En conséquence, la première partie de cette thèse traite des aspects méthodologiques et d’expérimentation de la mise en place d’un SP-ASP. Le système développé a été évalué pour la modélisation précise d’une gravière et utilisé pour réaliser des mesures de changement volumétrique. Cette application a été retenue pour deux raisons principales. Premièrement, ce type de milieu fournit un environnement difficile pour la modélisation, et ce, en termes de changement d’échelle, de changement de relief du terrain ainsi que la grande diversité de structures et de textures. Deuxièment, le suivi de mines à ciel ouvert exige un niveau de précision élevé, ce qui justifie les efforts déployés pour mettre au point un SP-ASP de haute précision. Les composantes matérielles du système consistent en un ASP à propulsion électrique de type hélicoptère, d’une caméra numérique à haute résolution ainsi qu’une station inertielle. La composante logicielle est composée de plusieurs programmes développés particulièrement pour calibrer la caméra et la plateforme, intégrer les systèmes, enregistrer les données, planifier les paramètres de vol et détecter automatiquement les points de contrôle au sol. Les détails complets du système sont abordés dans la thèse et des solutions sont proposées afin d’améliorer le système et la qualité des données photogrammétriques produites. La précision des résultats a été évaluée sous diverses conditions de cartographie, incluant le géoréférencement direct et indirect avec un nombre, une répartition et des types de points de contrôle variés. De plus, les effets de la configuration des images et la stabilité du réseau sur la précision de la modélisation ont été évalués. La deuxième partie de la thèse porte sur l’amélioration des techniques de reconstruction éparse et dense. Les solutions proposées sont des alternatives aux techniques de photogrammétrie aérienne traditionnelle et adaptée aux caractéristiques particulières de l’imagerie acquise à basse altitude par ASP. Tout d’abord, une méthode robuste de correspondance éparse et d’estimation de la géométrie épipolaire a été développée. L’élément clé de cette méthode est sa capacité à gérer le pourcentage très élevé des valeurs aberrantes (erreurs entre les points correspondants) avec une efficacité de calcul remarquable en comparaison avec les techniques usuelles. Ensuite, une stratégie d’ajustement de bloc basée sur l’intégration de pseudoobservations du modèle Gauss-Helmert a été proposée. Le principal avantage de cette stratégie consistait à contrôler les effets négatifs du réseau d’images instable et des images bruitées sur la précision de l’autocalibration. Une implémentation éparse de cette stratégie a aussi été réalisée, ce qui a permis de traiter des jeux de données contenant des millions de points de liaison. Finalement, les concepts de courbes intrinsèques ont été revisités pour l’appariement stéréo dense. La technique proposée pourrait atteindre un haut niveau de précision et d’efficacité en recherchant uniquement dans une petite portion de l’espace de recherche des disparités ainsi qu’en traitant les occlusions et les ambigüités d’appariement. Ces solutions photogrammétriques ont été largement testées à l’aide de données synthétiques, d’images à courte portée ainsi que celles acquises sur le site de la gravière. Le système a démontré sa capacité a modélisation dense de l’environnement avec une très haute exactitude en atteignant une précision 3D absolue de l’ordre de 11±7 mm

Reversible Computation: Extending Horizons of Computing

This open access State-of-the-Art Survey presents the main recent scientific outcomes in the area of reversible computation, focusing on those that have emerged during COST Action IC1405 "Reversible Computation - Extending Horizons of Computing", a European research network that operated from May 2015 to April 2019. Reversible computation is a new paradigm that extends the traditional forwards-only mode of computation with the ability to execute in reverse, so that computation can run backwards as easily and naturally as forwards. It aims to deliver novel computing devices and software, and to enhance existing systems by equipping them with reversibility. There are many potential applications of reversible computation, including languages and software tools for reliable and recovery-oriented distributed systems and revolutionary reversible logic gates and circuits, but they can only be realized and have lasting effect if conceptual and firm theoretical foundations are established first

Fault-tolerance and load management in a distributed stream processing system

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 187-199).Advances in monitoring technology (e.g., sensors) and an increased demand for online information processing have given rise to a new class of applications that require continuous, low-latency processing of large-volume data streams. These "stream processing applications" arise in many areas such as sensor-based environment monitoring, financial services, network monitoring, and military applications. Because traditional database management systems are ill-suited for high-volume, low-latency stream processing, new systems, called stream processing engines (SPEs), have been developed. Furthermore, because stream processing applications are inherently distributed, and because distribution can improve performance and scalability, researchers have also proposed and developed distributed SPEs. In this dissertation, we address two challenges faced by a distributed SPE: (1) faulttolerant operation in the face of node failures, network failures, and network partitions, and (2) federated load management. For fault-tolerance, we present a replication-based scheme, called Delay, Process, and Correct (DPC), that masks most node and network failures.(cont.) When network partitions occur, DPC addresses the traditional availability-consistency trade-off by maintaining, when possible, a desired availability specified by the application or user, but eventually also delivering the correct results. While maintaining the desired availability bounds, DPC also strives to minimize the number of inaccurate results that must later be corrected. In contrast to previous proposals for fault tolerance in SPEs, DPC simultaneously supports a variety of applications that differ in their preferred trade-off between availability and consistency. For load management, we present a Bounded-Price Mechanism (BPM) that enables autonomous participants to collaboratively handle their load without individually owning the resources necessary for peak operation. BPM is based on contracts that participants negotiate offline. At runtime, participants move load only to partners with whom they have a contract and pay each other the contracted price. We show that BPM provides incentives that foster participation and leads to good system-wide load distribution. In contrast to earlier proposals based on computational economies, BPM is lightweight, enables participants to develop and exploit preferential relationships, and provides stability and predictability.(cont.) Although motivated by stream processing, BPM is general and can be applied to any federated system. We have implemented both schemes in the Borealis distributed stream processing engine. They will be available with the next release of the system.by Magdalena Balazinska.Ph.D