Abstracting Geographic Information in a Data Rich World

1. Front Matter

   Pages i-xv

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2. Map Generalisation: Fundamental to the Modelling and Understanding of Geographic Space

   • William Mackaness, Dirk Burghardt, Cécile Duchêne

   Pages 1-15

3. Map Specifications and User Requirements

   • Sandrine Balley, Blanca Baella, Sidonie Christophe, Maria Pla, Nicolas Regnauld, Jantien Stoter

   Pages 17-52

4. Modelling Geographic Relationships in Automated Environments

   • Guillaume Touya, Bénédicte Bucher, Gilles Falquet, Kusay Jaara, Stefan Steiniger

   Pages 53-82

5. Data Structures for Continuous Generalisation: tGAP and SSC

   • Peter van Oosterom, Martijn Meijers, Jantien Stoter, Radan Šuba

   Pages 83-117

6. Integrating and Generalising Volunteered Geographic Information

   • Monika Sester, Jamal Jokar Arsanjani, Ralf Klammer, Dirk Burghardt, Jan-Henrik Haunert

   Pages 119-155

7. Generalisation Operators

   • Lawrence V. Stanislawski, Barbara P. Buttenfield, Pia Bereuter, Sandro Savino, Cynthia A. Brewer

   Pages 157-195

8. Process Modelling, Web Services and Geoprocessing

   • Nicolas Regnauld, Guillaume Touya, Nicholas Gould, Theodor Foerster

   Pages 197-225

9. Terrain Generalisation

   • Eric Guilbert, Julien Gaffuri, Bernhard Jenny

   Pages 227-258

10. Evaluation in Generalisation

    • Jantien Stoter, Xiang Zhang, Hanna Stigmar, Lars Harrie

    Pages 259-297

11. Generalisation in the Context of Schematised Maps

    • William Mackaness, Andreas Reimer

    Pages 299-328

12. Generalisation in Practice Within National Mapping Agencies

    • Cécile Duchêne, Blanca Baella, Cynthia A. Brewer, Dirk Burghardt, Barbara P. Buttenfield, Julien Gaffuri et al.

    Pages 329-391

13. Conclusion: Major Achievements and Research Challenges in Generalisation

    • Dirk Burghardt, Cécile Duchêne, William Mackaness

    Pages 393-403

14. Back Matter

    Pages 405-407

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Research in the field of automated generalisation has faced new challenges in recent years as a result of technological developments in web-based processing, new visualisation paradigms and access to very large volumes of multi-source data generated by sensors and humans. In these contexts, map generalisation needs to underpin ‘on-demand mapping’, a form of mapping that responds to individual user requirements in the thematic selection and visualisation of geographic information. It is this new impetus that drives the research of the ICA Commission on Generalisation and Multiple Representation (for example through its annual workshops, biannual tutorials and publications in international journals). This book has a coherent structure, each chapter focusing on core concepts and tasks in the map generalisation towards on-demand mapping. Each chapter presents a state-of-the-art review, together with case studies that illustrate the application of pertinent generalisation methodologies. Thebook addresses issues from data gathering to multi scaled outputs. Thus there are chapters devoted to defining user requirements in handling specifications, and in the application and evaluation of map generalisation algorithms. It explores the application of generalisation methodologies in the context of growing volumes of data and the increasing popularity of user generated content.

• Automated Generalisation
• Data Integration
• Generalisation Web Services
• Multiple Representation
• On-demand Mapping

“This book provides a really critical contribution to summarizing, conceptualizing, and discussing the main problems and solutions in map generalization to date. … I recommend this book to everyone who works with map generalization and wants to be productive in solving his or her tasks, as well as those who are interested in understanding short- and mid-term perspectives in map generalization developments.” (Timofey Samsonov, Cartographic Perspectives, Issues 80, 2015)

• Department of Geosciences, Institute of Cartography, Dresden, Germany

  Dirk Burghardt

• IGN COGIT laboratory, Saint-Mande, France

  Cécile Duchêne

• Geographical Information Science, School of GeoSciences, Edinburgh, United Kingdom

  William Mackaness

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