Map Production and Geoinformation Management

Varied Production Approaches

6602.1 - Maps and Models - The Art of automated Map Production using flexible Tools and Workflows

Thursday, July 6
2:50 PM - 3:10 PM
Location: Delaware B

Being a Federal Republic that put the responsibility for providing geodata, including maps on 16 federal states, Germany faces specific problems to produce and provide consistent national topographic and cartographic datasets. Due to this fact it is obvious that defined and agreed standards are essential to meet the requirements of users. The continuous efforts to optimize lead to the so called AAA-Modell, launched in 2006. Along with modeling rules for topographic objects and cadastre, map objects could be created and stored on the same topological database.
In parallel, driven by the necessity to produce maps more frequently and efficiently a party of 12 (states) joined together to find new ways of producing topographical maps, preferably supported by tools that allow 100% automated generalization. Apart from this one fundamental goal there were others such as
- Tools and Workflows must be adjustable to derive maps of different scales
- All map products are derived from the base digital landscape model (Basis-DLM)
- Generalization of a whole-state-dataset must be possible
Starting off with this vision the paper will show steps that were taken to really make it come true. We will be talking about ups and downs during a period of almost 9 years. Today all 12 participants use in one way or the other tools and workflows resulting from this cooperation named ATKIS-Generalisierung.

Maps and Models - there is no map without a correspondent digital landscape model that goes with it. This is why the process of production is split in two
- (mostly) Semantic Generalization of digital landscape models according to target scale. This workflow is called Modellgeneralisierung or simply Model.
- Cartographic Generalization of digital landscape model (target scale) for presentation according to presentation rules for topographic maps. This workflow is called Automatische Kartographische Generalisierung or simply Karto.
Model basically reduces objects and resolution of the base digital landscape model (Basis-DLM) by
- Merging objects according to predefined similarity or specifically defined rules
- Deleting objects according to feature catalogue or specifically defined rules
- Converting complex roads (consisting of single lanes) to simple roads and rebuilding topology
As a result of Model we get a whole state dataset (DLM50, DLM100), topologically correct and suitable for symbolization and further automated generalization using Karto.
Automating the process of cartographic generalization is a challenge that keeps us running. There is still work to do to further improve the results to better meet the requirements of high quality cartography. Almost 40 Data Cases describe in detail specific situations of graphical conflicts that need to be solved by generalization. Data Cases solve conflicts line – line, line – point, point – point and deal with area generalization for example enlargement, deletion or merging of areas.
Out of this toolbox of Data Cases a Karto-workflow can be built that best meets our expected result.
Both Model and Karto are controlled by parameters that can be changed through trained users. This is essential for being able to go towards generalization on demand – any choice of objects generalized for presentation in any choice of scale – maybe through the internet by any user, if we provided standardized workflows.
To be fair – today we still need to do some finishing work after running Karto, but having recently added functionality to generalize single buildings taken from the cadastre for a whole state we are moving forward. Step by step. We are sure presenting and discussing results at ICC will be another step towards 100%.

Barbara Greiner

Dezernatsleitung Geobasis DTK, Visualisierung
Hessisches Landesamt für Bodenmanagement und Geoinformation

In 1992 I gratuated as Dipl.-Ing. in Cartography at Hochschule Karlsruhe (University of Applied Sciences), Germany. in 1994 I joined the Hessische Verwaltung für Bodenmanagement und Geoinformation (HVBG) as part and later head of a team responsible for cartographic development focussing on optimizing workflows and tools for cartographic generalisation of topographic maps. Since 2003 I have been a member of the Technical Commitee within ATKIS-Generalisierung, a project linking together several federal states of Germany to provide solutions for automated generalisation.
At the moment, as head of cartography within HVBG, I take responibility for all Toporaphic Maps and any cartographic visualisation out of geospatial databases mapping the state of Hessen.
Throughout my career I have been involved with training of young people in cartography as well as data modelling and visualisation; currently as assistant professor at Frankfurt University of Applied Sciene, lecturing a course Geobasisdaten.


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Kristin A. Fishburn

Cartographic Products Lead
United States Geological Survey

Kristin Fishburn is the Cartographic Content Lead for the National Geospatial Program at the United States Geological Survey, providing strategy and vision for the US Topo map and Historical Topographic Map Collection programs and for cartographic design associated with The National Map. She earned her Master of Science degree in Cartography from The Ohio State University in 1992 and obtained her GIS Professional Certification (GISP) in 2008.


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6602.1 - Maps and Models - The Art of automated Map Production using flexible Tools and Workflows


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