This article presents a case study on harmonising and integrating two domain models topography in... more This article presents a case study on harmonising and integrating two domain models topography into a global model that have been established for different purposes; IM- Geo defines topography to serve municipalities in maintaining public and built-up area; TOP10NL defines topography for visualisation at 1:10k scale. The study identifies prob- lems and proposes solutions to accomplish integration, which is required
This article presents a case study on harmonising and integrating two domain models topography in... more This article presents a case study on harmonising and integrating two domain models topography into a global model that have been established for different purposes; IM-Geo defines topography to serve municipalities in maintaining public and built-up area; TOP10NL defines topography for visualisation at 1:10k scale. The study identifies problems and proposes solutions to accomplish integration, which is required to provide the datasets within the principles of the national Spatial Data Infrastructure. At first the types of differences between the current models are analysed. Secondly, the article formulates recommendations to harmonise the differences which may be random (i.e. easy to solve) or fundamental (to be addressed in the integration). Finally, the article presents modelling principles for an integrated model topography based on two conclusions of the comparison study: two domain models are necessary to meet the specific demands of the two domains and secondly, TOP10NL cannot be derived from IMGeo because differences in perspective proved to be more dominant than scale differences did. Both the recommendations for harmonisation and the modelling principles are illustrated with prototypes which show the problems and potentials of harmonising and integrating different local (national) data models into global models.
This article presents the results of integrating large-and medium-scale data into a unified data ... more This article presents the results of integrating large-and medium-scale data into a unified data structure. This structure can be used as a single non-redundant representation for the input data, which can be queried at any arbitrary scale between the source scales. The solution is based on the constrained topological Generalized Area Partition (tGAP), which stores the results of a generalization process applied to the large-scale dataset, and is controlled by the objects of the medium-scale dataset, which act as constraints on the large-scale objects. The result contains the accurate geometry of the large-scale objects enriched with the generalization knowledge of the medium-scale data, stored as references in the constraint tGAP structure. The advantage of this constrained approach over the original tGAP is the higher quality of the aggregated maps. The idea was implemented with real topographic datasets from The Netherlands for the large-(1:1000) and medium-scale (1:10,000) data. The approach is expected to be equally valid for any categorical map and for other scales as well.
This article presents a case study on harmonising and integrating two domain models topography in... more This article presents a case study on harmonising and integrating two domain models topography into a global model that have been established for different purposes; IM- Geo defines topography to serve municipalities in maintaining public and built-up area; TOP10NL defines topography for visualisation at 1:10k scale. The study identifies prob- lems and proposes solutions to accomplish integration, which is required
This article presents a case study on harmonising and integrating two domain models topography in... more This article presents a case study on harmonising and integrating two domain models topography into a global model that have been established for different purposes; IM-Geo defines topography to serve municipalities in maintaining public and built-up area; TOP10NL defines topography for visualisation at 1:10k scale. The study identifies problems and proposes solutions to accomplish integration, which is required to provide the datasets within the principles of the national Spatial Data Infrastructure. At first the types of differences between the current models are analysed. Secondly, the article formulates recommendations to harmonise the differences which may be random (i.e. easy to solve) or fundamental (to be addressed in the integration). Finally, the article presents modelling principles for an integrated model topography based on two conclusions of the comparison study: two domain models are necessary to meet the specific demands of the two domains and secondly, TOP10NL cannot be derived from IMGeo because differences in perspective proved to be more dominant than scale differences did. Both the recommendations for harmonisation and the modelling principles are illustrated with prototypes which show the problems and potentials of harmonising and integrating different local (national) data models into global models.
This article presents the results of integrating large-and medium-scale data into a unified data ... more This article presents the results of integrating large-and medium-scale data into a unified data structure. This structure can be used as a single non-redundant representation for the input data, which can be queried at any arbitrary scale between the source scales. The solution is based on the constrained topological Generalized Area Partition (tGAP), which stores the results of a generalization process applied to the large-scale dataset, and is controlled by the objects of the medium-scale dataset, which act as constraints on the large-scale objects. The result contains the accurate geometry of the large-scale objects enriched with the generalization knowledge of the medium-scale data, stored as references in the constraint tGAP structure. The advantage of this constrained approach over the original tGAP is the higher quality of the aggregated maps. The idea was implemented with real topographic datasets from The Netherlands for the large-(1:1000) and medium-scale (1:10,000) data. The approach is expected to be equally valid for any categorical map and for other scales as well.
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Papers by Arjen Hofman