Handling and Mapping Geographic Information

Claire Cunty is a lecturer and researcher in geography at the Université Lumière Lyon 2, France, and a member of the Environnement Ville Société research unit. Her research focuses on the design and use of geovisualization interfaces for spatiotemporal information and on digital approaches to sensitive maps. She is also part of the supervisory team for the Master’s program in Digital Geographies at Lyon 2 and SaintEtienne Universities.Hélène Mathian is a CNRS engineer in spatial analysis methods at the Environnement Ville Société research unit, France. Her work integrates the spatial dimension into statistical processing and models, and uses geovisualization as a means of exploring geographic data and spatial dynamics. She is also part of the supervisory team for the Master’s program in Digital Geographies at Lyon 2 and Saint-Etienne Universities.

• Foreword xiColette CAUVIN-REYMONDIntroduction xviiClaire CUNTY and Hélène MATHIANChapter 1. Exploring Statistical Relationships with Maps and Charts 1Jean-Benoît BOURON, Claire CUNTY, Hélène MATHIAN and Myriam BARON1.1. Introduction 11.2. Mapping the world: which world? what data? 41.3. Exploring data and relationships with maps and charts 111.4. Describing statistical relationships between several variables 181.5. Conclusion 251.6. References 26Chapter 2. Heterogeneous Data Integration and Geoweb Cartographic Representations 29Marianne GUÉROIS and Malika MADELIN2.1. Introduction 292.2. New data: from production to visualization 322.3. New data, traditional data: why and how to integrate them? 452.4. Conclusion 592.5. References 61Chapter 3. Environmental Data and Cartographic Objects 65Étienne COSSART3.1. Introduction 653.2. Building cartographic objects: deconstructing to reconstruct. 673.3. Dealing with disparate and incomplete data: examples from environmental geography 743.4. Conclusion 863.5. References 87Chapter 4. Mapping and Identifying Geographic Configurations: The Example of Segregation 89Sylvestre DUROUDIER4.1. Introduction 894.2. Mapping: rendering spatial configurations visible or invisible 914.3. How to measure a phenomenon so as to reveal its forms 1044.4. Capturing spatial forms using dynamic approaches 1164.5. Conclusion 1254.6. References 126Chapter 5. Map and Statistical Model to Explore Spatial Heterogeneity 131Mohamed HILAL and Julie LE GALLO5.1. Introduction 1315.2. From raw open-source data to statistical data 1335.3. Preliminary explorations of spatial variations 1395.4. Analyzing relationships statistically and rendering a map 1495.5. Conclusion 1685.6. References 169Chapter 6. Mapping Time 173Claire CUNTY and Hélène MATHIAN6.1. Introduction 1736.2. Formalization 1756.3. Monitoring territorial changes 1846.4. Representing phenomena associated with movement 1916.5. Representing temporality 1976.6. Conclusion 2066.7. References 209Chapter 7. Cartograms, Anamorphic Maps: Transformed Territories 217Anne-Christine BRONNER7.1. Introduction 2177.2. Cartograms to represent count data associated with areal units 2197.3. Anamorphic map for the representation of space-time 2347.4. Anamorphic maps, cartograms: cross-cutting reflections on common principles and reading difficulties 2477.5. Conclusion 2517.6. References 252Chapter 8. Exploration, Aggregation and Spatiotemporal Visualization of Big Data 257Claude GRASLAND8.1. Introduction 2578.2. Defining the object of study and selecting the corpus 2598.3. Crossing the "who" and "what" dimensions 2648.4. Crossing the "who", "what" and "when" dimensions 2668.5. Crossing the "who", "what" and "where" dimensions 2708.6. Graphs to represent co-location relationships 2758.7. Conclusion 2828.8. References 284Conclusion 287Claire CUNTY and Hélène MATHIANList of Authors 291Index 293