AUTOMATED DERIVATION OF A 1:300 000 TOPOGRAPHIC MAP FROM SWISS DLM VECTOR 200
M. Bobzien1, I. Petzold2, D. Burghardt2
1 - Axes Systems AG, Alpnach, Switzerland
2 - University of Zurich, GIS Department, Zurich, Switzerland
The National Mapping Agency of Switzerland (swisstopo) is currently undertaking a complete redesign its map production process in the project Optina-LK. The aim of the project is the automatic derivation of Digital Cartographic Models (DCM) of scales between 1:25 000 and 1:300 000. The sources are two Digital Landscape Models (DLM) of different resolutions with scales around 1:10 000 and 1:200 000. The automated derivation will be performed within a subproject called SysDab, in which all automated generalisation operations as well as the automated part of the incremental updating will be performed.
This paper presents a feasibility study on the derivation of the DCM300 as the basis for a map of scale 1:300 000 from the Vector200-DLM. The derivation process consists of several steps of transformation and generalisation, all performed automatically in one continuous process. The process includes model transformation from DLM to DCM, as well as various generalisation operations such as line simplification, line smoothing, aggregation, merging, displacement, and reclassification. Both models are stored in a newly created MRDB enriched with meta information about the applied generalisation operations. This information is used as a prerequisite for automated incremental updating.
A workflow management system orchestrates and controls the process. The result is a completely automatically derived DCM300. Specific cartographic demands can be fulfilled with manual editing afterwards.
The derivation process makes use of the results of two research projects – DRIVE and SerAX. The former focused on the automated generalisation processes with MRDB and automatic incremental update, the latter – which is still ongoing – focuses on the orchestration and control of generalisation processes with help of a workflow management system. This paper shows the results of the automated generalisation process. It discusses possibilities and limitations of the automation, including the requirements on the source data.