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This thesis examines the nature of freely available geospatial software and data in the context of disaster risk reduction and disaster management. The use of geospatial data is crucial to effective disaster management, from preparedness to response and recovery. The best methodologies and technologies are useless if they cannot be accessed and used by the people in need or interested. Global inequalities in the provision and use of digital data and information – the so-called Digital Divide - are examined by means of datasets from 2009 to 2013. Subsequently an innovative Data Poverty Index is presented as a metric to compare differences worldwide. The focus of the presented method is on the incorporation of information and communication technology variables; also considered are the number of people in a country who can make use of freely available digital resources due to their education, access to the Internet and required hardware. A significant contribution is the clear indication that the gap between the data-poor and the data-rich is currently widening. The highest population growth until 2050 is expected in developing countries, especially in Africa and Asia, the majority of them with coastlines. Therefore, the focus of this research is on coastal regions and methods that can be applied in developing countries. Having methods, data and software in place that can improve vulnerability mapping and highlight at-risk areas, helps to focus limited financial and expert resources. Although applied geoinformatics has demonstrated great potential for disaster risk reduction applications, only in recent years there has been a substantial shift away from crisis response towards disaster preparedness and mitigation. A free geoinformatics approach, combined with freely available training materials could assist the development of sustainable disaster management, which is advocated by the United Nations Sendai Framework for Disaster Risk reduction. A number of low-cost geoinformatics case studies, covering the Caribbean, the UK, Sierra Leone and Sri Lanka, demonstrate the potential of free geoinformatics as well as highlighting some limitations.

Despite the fact that we are in the mobile computing age, student geologists still carry out geological fieldwork using centuries old tools and techniques. This thesis investigates the question “how can 3D visualization on smartphones and tablets help students learn during geological fieldwork?” To answer this question, the thesis first reviews the types of difficulty encountered by novice geologists, narrowing it down to one particular issue: the extrapolation of 2D geological features into the 3D real world. The tasks carried out by novice geologists during introductory fieldwork were analysed systemically. This thesis then explored how apps from Android and iOS app stores may be used in the field to carry out such tasks. The overall finding is that there is limited work focused on novice geologists' difficulties during fieldwork, particularly 2D to 3D extrapolation. Then, using a perception test, the options of representing a single strike and dip measurement in a 3D environment is explored. The results of the test was that there were more accurate methods to represent a measurement than a traditional symbol (e.g. a T-shape). Then, a hypothesis was evaluated which states that instead of using 2D geological maps alone, a 3D visualization of strike and dip measurements plotted on them can assist students in understanding geological structures. The thesis then outlines functionality of a prototype that can be used by higher education institutions as a foundation for a novice geologists' field app. Key findings of the present work are: there has been no apps developed with focus on issues faced by novice geologists doing fieldwork during the time of this study. There was only British Geological Survey's iGeology3D which was released at the time of the study which focused on 3D visualization of geological data to be used in the field. In a separate study an iPad2 was found to be accurate enough for taking strike and dip measurements. In a perception experiment a 3D visualization of strike and dip was deemed to be better for comprehending structural orientation of outcrops but found to be no better than other 2D shapes. Finally, an experiment comparing the use of 2D maps versus 2D maps overlaid with 3D visualization of structural data, the latter found to be more effective for structural interpretation by novice geologists.

Die Gewinnung von regional- und landschaftsplanerischen Aussagen zu wichtigen Themen aus den Funktionsbereichen des Natur- und Landschaftsschutzes sowie der natürlichen Erholungseignung erfordert die Verknüpfung jeweils mehrerer thematischer Datenebenen. Im Rahmen einer Landschaftsstrukturanalyse werden die Freiflächenzerschneidung, die Biotopvernetzung und die Ökotonlängen in ihrer räumlichen Ausprägung ermittelt. Durch GIS-gestützte Verschneidungsalgorithmen können Problemareale erkannt werden, in denen sich Nutzungsansprüche überlagern (beispielsweise sensible Bereiche mit Baugebietsstandorten). Andererseits können Bereiche herausgearbeitet werden, die aufgrund ihrer vielfältigen landschaftshaushaltlichen Funktionen eine hohe Wertigkeit besitzen.

Die Gewinnung von regional- und landschaftsplanerischen Aussagen zu wichtigen Themen aus den Funktionsbereichen des Natur- und Landschaftsschutzes sowie der natürlichen Erholungseignung erfordert die Verknüpfung jeweils mehrerer thematischer Datenebenen. Im Rahmen einer Landschaftsstrukturanalyse werden die Freiflächenzerschneidung, die Biotopvernetzung und die Ökotonlängen in ihrer räumlichen Ausprägung ermittelt. Durch GIS-gestützte Verschneidungsalgorithmen können Problemareale erkannt werden, in denen sich Nutzungsansprüche überlagern (beispielsweise sensible Bereiche mit Baugebietsstandorten). Andererseits können Bereiche herausgearbeitet werden, die aufgrund ihrer vielfältigen landschaftshaushaltlichen Funktionen eine hohe Wertigkeit besitzen.

Les incertitudes épistémiques peuvent être réduites via des études supplémentaires (mesures labo, in situ, ou modélisations numériques, etc.). Nous nous concentrons ici sur celle "paramétrique" liée aux difficultés à évaluer quantitativement les paramètres d’entrée du modèle utilisé pour l’analyse des aléas géotechniques. Une stratégie de gestion possible est l’analyse de sensibilité, qui consiste à identifier la contribution (i.e. l’importance) des paramètres dans l’incertitude de l’évaluation de l’aléa. Des approches avancées existent pour conduire une telle analyse. Toutefois, leur application au domaine des aléas géotechniques se confronte à plusieurs contraintes : 1. le coût calculatoire des modèles numériques (plusieurs heures voire jours) ; 2. les paramètres sont souvent des fonctions complexes du temps et de l’espace ; 3. les données sont souvent limitées, imprécises voire vagues. Dans cette thèse, nous avons testé et adapté des outils statistiques pour surmonter ces limites. Une attention toute particulière a été portée sur le test de faisabilité de ces procédures et sur la confrontation à des cas réels (aléas naturels liés aux séismes, cavités et glissements de terrain) / Importance ranking of parameter uncertainties in geo-hazard assessments Epistemic uncertainty can be reduced via additional lab or in site measurements or additional numerical simulations. We focused here on parameter uncertainty: this corresponds to the incomplete knowledge of the correct setting of the input parameters (like values of soil properties) of the model supporting the geo-hazard assessment. A possible option tomanage it is via sensitivity analysis, which aims at identifying the contribution (i.e. the importance) of the different input parameters in the uncertainty on the final hazard outcome. For this purpose, advanced techniques exist, namely variance-basedglobal sensitivity analysis. Yet, their practical implementation faces three major limitations related to the specificities of the geo-hazard domain: 1. the large computation time cost (several hours if not days) of numerical models; 2. the parameters are complex functions of time and space; 3. data are often scarce, limited if not vague. In the present PhD thesis, statistical approaches were developed, tested and adapted to overcome those limits. A special attention was paid to test the feasibility of those statistical tools by confronting them to real cases (natural hazards related to earthquakes, cavities and landslides)

De nos jours, la préservation de l’environnement constitue un enjeu prioritaire. La compréhension des phénomènes environnementaux passe par l’étude et la combinaison d’un nombre croissant de données hétérogènes. De nombreuses initiatives internationales (INSPIRE, GEOSS) visent à encourager le partage et l’échange de ces données. Dans ce sujet de recherche, nous traitons de l’intérêt de mettre à disposition des modèles scientifiques sur le web. Nous montrons l’intérêt d’utiliser des applications s’appuyant sur des données géoréférencées et présentons des méthodes et des moyens répondant aux exigences d’interopérabilité. Nous illustrons notre approche par l’implémentation de modèles d’estimation des besoins en eau agricoles et domestiques fonctionnant à diverses échelles spatiales et temporelles. Un prototype basé sur une architecture entièrement orientée services web a été développé. L’outil s’appuie sur les standards Web Feature Service (WFS), Sensor Observation Service (SOS) et Web Processing Service (WPS) de l’OGC. Enfin, la prise en compte des imperfections des données est également abordée avec l’intégration de méthodes d’analyse de sensibilité et de propagation de l’incertitude. / Nowadays, preservation of the environment is a main priority. Understanding of environmental phenomena requires the study and the combination of an increasing number of heterogeneous data. Several international initiatives (INSPIRE, GEOSS) aims to encourage the sharing and exchange of those data.In this thesis, the interest of making scientific models available on the web is discussed. The value of using applications based on geospatial data is demonstrated. Several methods and means that satisfy the requirements of interoperability are also purposed.Our approach is illustrated by the implementation of models for estimating agricultural and domestic water requirements. Those models can be used at different spatial scales and temporal granularities. A prototype based on a complete web service oriented architecture was developed. The tool is based on the OGC standards Web Feature Service (WFS), Sensor Observation Service (SOS) and Web Processing Service (WPS).Finally, taking into account the imperfections of the data is also discussed with the integration of methods for sensitivity analysis and uncertainty propagation.