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Affiner la recherche Interroger des sources externesEnhancing knowledge, skills, and spatial reasoning through location-based mobile learning / Christian Sailer (2020)
Titre : Enhancing knowledge, skills, and spatial reasoning through location-based mobile learning Type de document : Thèse/HDR Auteurs : Christian Sailer, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2020 Collection : Dissertationen ETH num. 26817 Importance : 289 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse géovisuelle
[Termes IGN] apprentissage (cognition)
[Termes IGN] enseignement secondaire
[Termes IGN] plateforme logicielle
[Termes IGN] programme interactif
[Termes IGN] raisonnement spatialRésumé : (auteur) Location-based mobile learning (LBML) involves learning in and about locations in order to explore, analyze, describe, and evaluate phenomena in authentic learning experiences and incorporate them into the real world. Learners gain an understanding of boththe immediate environment using all the senses and the spatial perception to create a holistic impression of the environmental phenomena. Mobile mapping technologies and location-based services are utilized to link learning contents to specific locations as stories, tasks, or assignments. A large number of research projects on mobile learning have investigated LBML systems and LBML approaches with regard to learner satisfaction, usability and efficiency. The projects achieved predominantly positive results regarding motivation and engagement but only fragmented results regarding the cognitive learning outcomes.This dissertation describes how an LBML system utilizing GIS technology enhances the educational learning outcomes with a special focus on the spatial thinking process. Furthermore, this dissertation describes novel approaches of visual analytics with 2D and 3D map web components to produce new teaching strategies during the activities and new metacognitive strategies to evaluate and reflect the activity. The study presented in this dissertation covers case studies in universities, vocational schools, and informal education environments using design-based research to develop a mobile-friendly interactive mapping platform. Furthermore, the platform includes multimedia capabilities and interfaces to connect external services and content. The main study was conducted in a secondary school under real conditions and evaluated the technology regarding the learning performance and the teaching activities before, during, and after the activity. The results reveal a better cognitive learning outcome in classroom exams when a teaching sequence of several weeks includes an outdoor activity of a double lesson. Moreover, there is potential for enhancing learning beyond the outdoor part to improve spatial reasoning. Long-term self-assessment of the learners, however, resulted in no impact, whether cognitively or affectively. The workload for outdoor teaching compared to classroom teaching is higher mainly due to the profound inspections of the location. The findings and their implications for research and teacher education were discussed in order to corroborate the educational value of LBML to motivate educators using LBML strategies for teaching. Numéro de notice : 17657 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse étrangère Note de thèse : doctoral thesis : Geomatics : ETH Zurich : 2020 En ligne : http://dx.doi.org/10.3929/ethz-b-000458558 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97924
Titre : Modelling historical accessibility and its effects in space Type de document : Thèse/HDR Auteurs : Raphaël Fuhrer, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2020 Collection : Dissertationen ETH num. 26093 Importance : 187 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] accessibilité
[Termes IGN] analyse comparative
[Termes IGN] analyse diachronique
[Termes IGN] carte ancienne
[Termes IGN] corrélation
[Termes IGN] données anciennes
[Termes IGN] réseau de transportRésumé : (auteur) This thesis deals with the modelling of historical accessibility values, covering Switzerland and neighbouring regions from today until 1720. Changes in transport supply have spatial e ects on environment, society and economy; many of them are persistent. There are methods to quantify, isolate and capture causality. However, related studies are rarely done, one reason for that being missing data. The thesis details methods to reconstruct historical transport networks and corresponding travel system times. The related techniques, relevant conditions in historical transport maps and procedures needed are explained in detail. The associated numbers related to development in transport and travelling are prepared. The thesis shows applications of such results regarding state reach and productivity gains. The accessibility model includes both transport on the main road network as well as the space in-between capturing all relevant transport modes and generating continuous results for long-distance travel. Results show strong border e ects; this might be due to the population distribution model or the rather flat weight function. Results show an increase of accessibility over time, following the networks available at the time and along the central axes. Numéro de notice : 17656 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse étrangère Note de thèse : Doctoral thesis : Sciences : ETH Zurich : 2020 En ligne : http://dx.doi.org/10.3929/ethz-b-000406184 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97916
Titre : Advanced modeling and algorithms for high-precision GNSS analysis Type de document : Thèse/HDR Auteurs : Kan Wang, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2016 Collection : Dissertationen ETH num. 23188 Note générale : bibliographie
thesis submitted to attain the degree of doctor of sciences of ETH ZurichLangues : Anglais (eng) Descripteur : [Termes IGN] ambiguïté entière
[Termes IGN] antenne GPS
[Termes IGN] centre de phase
[Termes IGN] données BeiDou
[Termes IGN] données Galileo
[Termes IGN] données GPS
[Termes IGN] double différence
[Termes IGN] erreur systématique
[Termes IGN] GPS en mode différentiel
[Termes IGN] horloge
[Termes IGN] phase GNSS
[Termes IGN] positionnement cinématique
[Termes IGN] récepteur GNSS
[Termes IGN] récepteur trifréquence
[Termes IGN] résolution d'ambiguïté
[Termes IGN] retard ionosphèrique
[Termes IGN] Suisse
[Termes IGN] trajet multiple
[Vedettes matières IGN] Traitement de données GNSSRésumé : (auteur) In the recent ten years, the Global Navigation Satellite System (GNSS) processing has experienced a fast development in many areas including the increasing number of frequencies, the higher quality of positioning instruments, e.g. the receiver clocks and the satellite clocks, and more integrated modeling and calculation strategies. This thesis includes investigations of different modeling and parameterization methods in modern GNSS positioning with the focus on three important positioning error sources: the receiver clock errors, the phase ambiguities and the ionospheric delays.
The thesis shows that making use of the high-quality receiver clocks and applying appropriate receiver clock modeling can help to improve the kinematic height estimates, which are highly correlated with the receiver clock parameters. An efficient pre-elimination and back-substitution strategy of epoch parameters with relative clock constraints between subsequent and near-subsequent epochs has been developed to enable processing of, e.g., high-rate data. A detailed analysis of the relationship between the clock quality and the improvement of kinematic heights has been performed. Studies were also conducted to decorrelate the receiver clock parameters, the kinematic heights and the troposphere parameters. Experiments with real data have shown that appropriate deterministic and stochastic clock models can also be helpful to increase the resolution of the estimated Zenith Path Delay (ZPD) parameters without obvious degradation of the stability of the kinematic heights.
The second aspect of the thesis focuses on the resolution of triple-frequency phase ambiguities with different linear combinations. A complete analytical investigation of Geometry-Free (GF) and Ionosphere-Free (IF) triple-frequency phase ambiguity resolution with minimized noise level has been performed for different frequency triplets. The analysis was done separately for the best two linear combinations and the third one. Experiments have shown that the fractional parts and the formal errors of the combined ambiguities of the best two linear combinations are relatively small for Galileo E1, E5b and E5a and GPS L1, L2 and L5 triplets, while the third linear combination remains a challenge. Further analysis with the geostationary satellites of the Beidou Navigation Satellite System (BDS) elaborated in the framework of this thesis has also confirmed that the combined ambiguities from the best two GF and IF linear combinations can be fixed by rounding, while the estimated ambiguities on L1 have relatively large deviations from the values obtained from the traditional dual-frequency double-difference ambiguity resolution. Apart from the triple-frequency ambiguity resolution on the double-difference level, the so-called track-to-track ambiguities between different tracks of the same receiver and the same satellite have also been investigated for the best two triple-frequency linear combinations using GPS L1, L2 and L5 as well as Galileo E1, E5b and E5a observations. The outcome demonstrates that elevation-dependent influences on the observations like Phase Center Variations (PCVs), Phase Center Offsets (PCOs) and multipath are important for the fixing of the track-to-track ambiguities.
The combined track-to-track ambiguities using the best two linear combinations are also effective in detecting problems in the observation data.
The third aspect of the thesis includes the investigation of the differential ionospheric delays and gradients in the region of Switzerland from 1999 to 2013. In differential Global Positioning System (GPS) positioning, the ionospheric delays for short baselines are in most cases small enough to be ignored, except under extreme conditions, e.g., during ionospheric stormy days, and for applications with high integrity requirements, e.g., during approach and landing of aircrafts. This thesis introduces an algorithm using double-difference phase measurements with resolved phase ambiguities and global ionosphere maps provided by the Center for Orbit Determination in Europe (CODE) to extract the single-difference ionospheric delays, and enabling an automatic and robust processing of the data over 15 years. The results show that the daily maximum slant ionospheric gradients calculated from the differential slant ionopheric delays and the baseline lengths from 1999 to 2013 are below the slant ionosphere gradient boundary of the Conterminous United States (CONUS) ionospheric anomaly threat model.Numéro de notice : 17250 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse étrangère Note de thèse : dissertation : sciences : ETH Zurich : 2016 En ligne : http://dx.doi.org/10.3929/ethz-a-010610972 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81986
Titre : Algorithms for vision-based path following along previously taught paths Type de document : Thèse/HDR Auteurs : Deon George Sabatta, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2015 Collection : Dissertationen ETH num. 22391 Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to attain the degree of doctor of sciences of ETH ZurichLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] base de données d'images
[Termes IGN] calcul d'itinéraire
[Termes IGN] chemin le plus court, algorithme du
[Termes IGN] lacet
[Termes IGN] milieu urbain
[Termes IGN] navigation autonome
[Termes IGN] optimisation (mathématiques)
[Termes IGN] vision par ordinateurRésumé : (auteur) This thesis focusses on the task of navigating an autonomous vehicle along a previously driven path using feedback obtained from a camera system. The desired path is stored in the form of a “visual memory”, essentially a collection of images, captured when the vehicle was first driven along the path. Algorithms of this form find applications in many semi-autonomous inspection/exploration tasks, where the vehicle is initially navigated by an operator, using the visual data for other purposes. On completion of the task, the operator has provided the autonomous vehicle with all the information it needs to find its way back to the starting location, and potentially repeat the entire trip. By using reference images recorded along the initial path, the system is afforded a form of global localisation using only local sensing, by providing relative information to specific key-points within the environment.
The work presented in this thesis uses, as a base, two well established path following controllers, and extends these control algorithms into the visual domain, by deriving the required parameters of each of the controllers from information gathered in the images. One of the key focus points of this work is the use of only the bearing (yaw) information from the images. By only working with feature bearing information we essentially reduce the number of parameters by half (by ignoring elevation) without sacrificing performance on 2D-manifolds.
The first controller extends the well-known shortest distance to path control algorithm, by deriving a scaled distance to path and relative orientation from the visual memory. Using the scaled distance to path, we incorporate the unknown scale that typically plagues vision-based systems, into the controller to remove the velocity dependence of the control law. This algorithm was implemented and tested in an indoor environment with a motion capture system.
The second controller extends a model predictive control (MPC) based algorithm, derived during the 2007 DARPA Grand Challenge and initially reliant on GPS information, to make use of image data, thereby alleviating the need for GPS position information. To achieve this, a novel image-based cost function is proposed that can relate the relative distances between several images. This cost function guides the choice of control trajectories to minimise the computed cost from the reference path. The performance of the proposed cost function is examined in detail, including the effects of the number of features, average distance to feature, feature observation noise and the number of outliers.
To use this cost function, the control algorithm also needs an indication of how future actions will affect the cost, and to this end feature extrapolation becomes necessary. With limited visual information, and short baselines, this process is often not very successful, and various techniques are presented to improve the performance. These include the weighting of features based on their error prediction, and the reduction of the prediction horizon required by the controller.
This control algorithm was demonstrated in both urban and extra-urban settings over paths on the order of 400m where the performance is shown to be comparable to that of differential GPS. Finally, it is also shown how the algorithm can be simply adapted to incorporate collision avoidance behaviour during the path replay in the event that the environment has changed between recording and playback.Numéro de notice : 17201 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Thèse étrangère Note de thèse : Doctoral thesis : Sciences : ETH Zurich : 2015 En ligne : http://dx.doi.org/10.3929/ethz-a-010419338 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81177
Titre : Data-driven feature learning for high resolution urban land-cover classification Type de document : Thèse/HDR Auteurs : Piotr Andrzej Tokarczyk, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2015 Collection : Dissertationen ETH num. 22544 Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to attain the degree of doctor of sciences of ETH ZurichLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse en composantes principales
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] environnement de développement
[Termes IGN] image à très haute résolution
[Termes IGN] image à ultra haute résolution
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] prise en compte du contexte
[Termes IGN] ruissellement
[Termes IGN] surface imperméable
[Termes IGN] théorie de Dempster-ShaferRésumé : (auteur) Automated classification of aerial and satellite images is one of the fundamental challenges in remote sensing research. Over the last 30 years, researchers have tried to overcome the tedious and time consuming manual interpretation of images. With the advent of digital technologies, classification approaches facilitating image interpretation have emerged. They were quickly embraced, and nowadays classification of remote sensing imagery is a mature field with many well-established methods. However, a major yet largely unsolved problem is the design and selection of features, that would be appropriate for a specific classification task. Usually, it is not known in advance which image features would help separating object classes in an optimal way and manual feature by trial and error is still a common practice. In the last decade rapid development of remote sensing sensors gave the end-user access to very high resolution imagery. At a ground sampling distance below a meter, small objects and ne-grained texture of larger objects emerge. Thus, to properly exploit the information that these images contain, additional contextual and textural properties of objects should be extracted. Unfortunately, classification of such images is often performed using features tailored to low- and medium resolution sensors: raw pixel values, usually augmented with either simple band ratios (e.g. in form of vegetation indices), or specific texture filter banks (e.g. Gabor filters).
In this thesis, we consider the problem of feature design and selection for classification of urban land-cover from very high resolution (VHR) remote sensing images. To appropriately capture characteristic object patterns, we propose a set of simple and efficient features, called random quasi-exhaustive (RQE) feature bank. It consists of a multitude of multiscale texture features computed efficiently via integral images inside a sliding window. At the same time, we propose to sidestep manual feature selection, and let a boosting classifier choose only those features from a RQE feature bank that are able to efficiently discriminate between different object classes in a specific classification task. We believe that the proposed feature set is fairly generic to many urban remote sensing datasets, such that the features selected by the classifier can be adapted to the characteristics of a certain image: different lighting or different scene structures.
We start with presenting the developed framework for supervised classification of land-cover in urban environments. We demonstrate the efficiency of a boosting classifier used in conjunction with the RQE feature databank on five different very high resolution remote sensing datasets. Next, we move from supervised feature learning to unsupervised methods. Using random forest classifier, we investigate the performance of features extracted using data-driven methods, such as principal component analysis (PCA) or Deep Belief Networks (DBN). We show that, at least in our study, complex unsupervised and non-linear feature learning did not improve classification accuracy over standard linear baseline methods. Finally, we use the developed supervised classification framework for an application in the field of urban hydrology. We produce imperviousness maps, which are then used to model rainfall-runoff processes in urban catchments. We show that the proposed method yields results superior over state-of-the-art methods in the field of urban hydrology. Furthermore, we perform an end-to-end comparison, in which different image data sources produced using different classification methods are used as an input for a hydraulic sewer model.Numéro de notice : 17202 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : Doctoral thesis : Sciences : ETH Zurich : 2015 En ligne : http://dx.doi.org/10.3929/ethz-a-010414770 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81178 Modellhafte Arbeitsabläufe zur digitalen Erstellung von topographischen und geologischen Karten und dreidimensionalen Visualisierungen / Lorenz Hurni (1995)
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