Generalisation and Multiple Representation

Generalisation models and processes

6104.1 - Experiments to Distribute Map Generalization Processes

Thursday, July 6
8:30 AM - 8:50 AM
Location: Virginia B

Automatic map generalization requires the use of computationally intensive processes often unable to deal with large datasets. Distributing the generaliza-tion process is the only way to make them scalable and usable in practice. But map generalization is a highly contextual process, and the surroundings of a generalized map feature needs to be known to generalize the feature, which is a problem as distribution might partition the dataset and parallelize the pro-cessing of each part. This paper proposes experiments to evaluate the past propositions to distribute map generalization, and to identify the main re-maining issues. The past propositions to distribute map generalization are first discussed, and then the experiment hypotheses and apparatus are described. The experiments confirmed that regular partitioning was the quickest strategy, but also the less effective in taking context into account. The geographical partitioning, though less effective for now, is quite promising regarding the quality of the results as it better integrates the geographical context.

Guillaume Touya

Senior Researcher
IGN France, LASTIG, COGIT team

Guillaume Touya is a senior researcher at the LASTIG, COGIT team, IGN France (the French mapping agency). He holds a PhD in GI science from Paris-Est University. His research interests focus on automated cartography, map generalization and volunteered geographic information. He currently leads the MapMuxing (https://mapmuxing .ign.fr) research project.

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Justin Berli

IGN France, LASTIG, COGIT team

Justin Berli was a Master student from University of Orleans in internship at COGIT team.

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Imran Lokhat

IGN France, LASTIG, COGIT team

Imran Lokhat has been an IT developer at COGIT team since 2014. He manages the team's open source platform GeOxygene, and assists researchers on parallel processing and emerging cloud technologies.

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Nicolas Regnauld

Product Manager
1Spatial

Nicolas Regnauld has many years of experience in researching solutions for automating generalisation. After a PhD on generalisation at IGN (Paris), and a post Doctorate at the University of Edinburgh, he led the research team on automated generalisation at Ordnance Survey for 11 years. During this time, his team successfully developed a fully automated generalisation process that was used for the creation of OS VectorMap District. Nicolas is now Product Manager at 1Spatial, responsible for 1Generalise and 1Publish. These two products form the core of 1Spatial map derivation solutions, for deriving high quality maps from large geospatial databases.

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Cécile Duchêne

Senior Researcher
IGN France, LASTIG, COGIT team

Cécile Duchêne is a senior researcher at the LASTIG laboratory, COGIT team, IGN France (the French National Mapping Agency). She holds a PhD in computer science from University Pierre et Marie Curie (Paris 6) and an Habilitation from University Paris-Est. She has been the vice-chair of the ICA Commission on Generalisation and Multiple Representation since 2011. Her research interests are in automated spatial analysis and automated cartography, especially automated cartographic generalization.

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