Generalisation and Multiple Representation

Production, Generalization, and Conflation

6704.1 - Automatic map generalisation from research to production

Thursday, July 6
4:10 PM - 4:30 PM
Location: Virginia B

Automatic map generalisation from research to production
Authors: Mikael Johansson, Yang Zhang and Rose Nyberg, Lantmäteriet, Sweden

The manually work of map generalisation is known to be a complex and time consuming task. With the develop-ment of technology and societies, the demands of more flexible map products with higher quality are growing. The Swedish mapping, cadastral and land registration authority Lantmäteriet has manual production lines for data-bases in five different scales, 1:10 000 (SE10), 1:50 000 (SE50), 1:100 000 (SE100), 1:250 000 (SE250) and 1:1 million (SE1M). To streamline this work, Lantmäteriet started a project to automatically generalise geographic in-formation. Planned timespan for the project is 2015-2022.

There are several purposes with automatic generalisation; to have a more flexible production line; to produce prod-ucts that are possible to use in a more flexible way; to increase the efficiency in production and in the process of developing new products. At the same time the databases need to be modernized and improved. We do not know which products will be in demand in the future, but with harmonized and comprehensive databases with flexible structure and data of high quality, we will be better prepared for the future.

We have analysed the state of the art in automatic generalisation and have learnt from other mapping agencies that have worked with this for a while, e.g. collaborating with the experts at Dutch Kadaster, who have paved the way for us by showing that much of what we want to do is possible. We also got knowledge from our contacts with various universities and from participating in European projects (for instance the project European Location Framework) and other European collaboration initiatives.
To be able to succeed the basic geographic information in SE10 must be extended to cover the geographic infor-mation now only present in the other scales. Attributes and domain values must be synchronized to be able to store necessary information. The development environment is ArcGIS Desktop / ModelBuilder/ ArcObjects, FME, Py-thon with version handling in GIT.

Results and conclusions
This entry attempts to introduce how the generalisation of SE10 to SE50 of the dataset Land cover has been pro-cessed. The work continuing with Hydrography, Roads and Buildings and the other themes to complete SE50. In the future plans are formed for the generalisation of SE100, SE250 and SE1M.
With the project still ongoing, we can sum up our experiences after the first stage. Apart from increased knowledge about the techniques and the subject automatic map generalisation, there are other aspects to consider. The defini-tion of a common project target is important in a project with people with different backgrounds, to reach consen-sus. There are many dependencies to other parts of the organization and other ongoing projects (3D, product devel-opment, deliveries, production lines etc.) and to other initiatives in the geographical data field (standardisations) that are necessary to monitor. By collaborating with others and by taking advantage of other people's knowledge, such as participating in conferences and in international cooperation, we can improve both our products and our way of working.

Keywords: Automatic map generalisation, ArcGIS, ModelBuilder, Flexible products, National mapping agency, Sweden

Rose Nyberg

Senior Systems Analyst

Rose Nyberg, Senior Systems Analyst and GIS Specialist at Lantmäteriet, Sweden
Have been working in GIS development more than 30 years in different programming languages, beginning with Fortran, through Fortran77, C and C++ to current C#, Python and Javascript.
Current platform is ArcGIS, Desktop and Portal.
Experience from GIS system specification work in Botswana.


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Yang Zhang

GIS specialist

Yang Zhang is a GIS specialist at the Swedish national mapping agency Lantmäteriet and obtained his MSc degree(GIS and Cartography) in 2012. He is a member of the research and development team that investigates the automated map generalisation. He work both in Arcgis model builder and method developer.


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Nicolas Regnauld

Product Manager

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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6704.1 - Automatic map generalisation from research to production


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