Un défi majeur pour l'homme est de se munir de représentations de l'espace dans lequel il vit qui dépassent la représentation que lui-même peut s'en construire afin d'agir en étant mieux informé. Ces représentations doivent être partageables afin que les décisions bénéficient d'une variété de points de vue. Alors que les cartes deviennent numériques et que leur analyse peut être partagée entre l'homme et l'ordinateur, demeurent des défis concernant la représentation des données numériques sur l'espace, l'acquisition et le traitement de ces données. Cet ouvrage présente des développements logiciels majeurs produits récemment en géomatique, discipline à la croisée de la géographie et de l'informatique et qui se concentre sur l'acquisition et le traitement des données sur l'espace. Il analyse les spécificités de ces logiciels en termes de motivations, de modélisation de l'information et de méthodes d'analyse. Les verrous associés à leur mutualisation sont également analysés et conduisent à des propositions pour une meilleure mutualisation des efforts de recherche et de développement en géomatique.

This SpringerBrief discusses the characteristics of spatiotemporal movement data, including uncertainty and scale. It investigates three core aspects of Computational Movement Analysis: Conceptual modeling of movement and movement spaces, spatiotemporal analysis methods aiming at a better understanding of movement processes (with a focus on data mining for movement patterns), and using decentralized spatial computing methods in movement analysis. The author presents Computational Movement Analysis as an interdisciplinary umbrella for analyzing movement processes with methods from a range of fields including GIScience, spatiotemporal databases and data mining. Key challenges in Computational Movement Analysis include bridging the semantic gap, privacy issues when movement data involves people, incorporating big and open data, and opportunities for decentralized movement analysis arising from the internet of things. The interdisciplinary concepts of Computational Movement Analysis make this an important book for professionals and students in computer science, geographic information science and its application areas, especially movement ecology and transportation research.

Geosimulation is hailed as ‘the next big thing’ in geographic modelling for urban studies. This book presents readers with an overview of this new and innovative field by introducing the spatial modelling environment and describing the latest research and development using cellular automata and multi-agent systems. Extensive case studies and working code is available from an associated website which demonstrate the technicalities of geosimulation, and provide readers with the tools to carry out their own modelling and testing. The first book to treat urban geosimulation explicitly, integrating socio-economic and environmental modelling approaches Provides the reader with a sound theoretical base in the science of geosimulation as well as applied material on the construction of geosimulation models Cross-references to an author-maintained associated website with downloadable working code for readers to apply the models presented in the book Visit the Author's Website for further information on Geosimulation, Geographic Automata Systems and Geographic Automata Software http://www.geosimulationbook.com

By modeling pedagogical scenarios as directed geometrical graphs and proposing an associated modeling language, this book describes how rich learning activities, often designed for small classes, can be scaled up for use with thousands of participants. With the vertices of these graphs representing learning activities and the edges capturing the pedagogical relationship between activities, individual, team, and class-wide activities are integrated into a consistent whole. The workflow mechanisms modeled in the graphs enable the construction of scenarios that are richer than those currently implemented in MOOCs. The cognitive states of learners in two consecutive activities feed a transition matrix, which encapsulates the probability of succeeding in the second activity, based on success in the former. This transition matrix is summarized by a numerical value, which is used as the weight of the edge. This pedagogical framework is connected to stochastic models, with the goal of making learning analytics more appealing for data scientists. However, the proposed modeling language is not only useful in learning technologies, it also allows researchers in learning sciences to formally describe the structure of any lesson, from an elementary school lesson with 20 students to an online course with 20,000 participants.

Protected areas are at the base of the most national and international conservation strategies. Due to the many unpredictable elements in ecology matters, each protected area requires a case-specific set of guidelines but a common issue is how to cope with human interaction. The management of protected areas is replete with challenges and the only way to gain understanding and achieve greater management possibilities is to exchange experiences and knowledge. Environmental managers are aware of that and together with scientists are looking for more modern and better solutions, both with respect to natural resources and human interactions in many issues regarding nature protection. This publication presents reviews and research results on protected areas management, as well as 12 case studies derived from around the world with the aim of improving management effectiveness of the protected areas.

At a time when people use more and more geographic information and tools, the management of geographical information in software systems still holds many challenges and motivates researchers from different backgrounds to propose innovative solutions. Representing geographical space beyond our mere perception is key to making relevant decisions, whether it is with respect to sustainable development or to the planning of everyday activities. Designing, sharing and exploiting such representations entails many challenges. This book presents recent software design projects, led in teams, which sometimes have different backgrounds, to address these challenges. It analyzes the specificities of these projects in terms of motivation, data models and analysis methods. Proposals are also put forward to improve resource sharing in this domain. Contents 1. Introduction, Bénédicte Bucher and Florence Le Ber. Part 1. Software Presentation 2. ORBISGIS: Geographical Information System Designed by and for Research, Erwan Bocher and Gwendall Petit. 3. GEOXYGENE: an Interoperable Platform for Geographical Application Development, Éric Grosso, Julien Perret and Mickaël Brasebin. 4. Spatiotemporal Knowledge Representation in AROM-ST, Bogdan Moisuc, Alina Miron, Marlène Villanova-Olivier and Jérôme Gensel. 5. GENGHIS: an Environment for the Generation of Spatiotemporal Visualization Interfaces, Paule-Annick Davoine, Bogdan Moisuc and Jérôme Gensel. 6. GEOLIS: a Logical Information System to Organize and Search Geo-Located Data, Olivier Bedel, Sébastien Ferré and Olivier Ridoux. 7. GENEXP-LANDSITES: a 2D Agricultural Landscape Generating Piece of Software, Florence Le Ber and Jean-François Mari. 8. MDWEB: Cataloging and Locating Environmental Resources, Jean-Christophe Desconnets and Thérèse Libourel. 9. WEBGEN: Web Services to Share Cartographic Generalization Tools, Moritz Neun, Nicolas Regnauld and Robert Weibel. Part 2. Summary and Suggestions 10. Analysis of the Specificities of Software Development in Geomatics Research, Florence Le Ber and Bénédicte Bucher. 11. Challenges and Proposals for Software Development Pooling in Geomatics, Bénédicte Bucher, Julien Gaffuri, Florence Le Ber and Thérèse Libourel.