Geographic data themes modelled as planar partitions are found in many GIS applications (e.g. topographic data, land cover, zoning plans, etc.). When generalizing this kind of 2D map, this specific nature has to be respected and generalization operations should be carefully designed. This paper presents a design and implementation of an algorithm to perform a split operation of faces (polygonal areas). The result of the split operation has to fit in with the topological data structure supporting variable-scale data. The algorithm, termed SPLITAREA, obtains the skeleton of a face using a constrained Delaunay triangulation. The new split operator is especially relevant in urban areas with many infrastructural objects such as roads. The contribution of this work is twofold: (1) the quality of the split operation is formally assessed by comparing the results on actual test data sets with a goal/metric we defined beforehand for the ‘balanced’ split and (2) the algorithm allows a weighted split, where different neighbours have different weights due to different compatibility. With the weighted split, the special case of unmovable boundaries is also explicitly addressed. The developed split algorithm can also be used outside the generalization context in other settings. For example, to make two cross-border data sets fit, the algorithm could be applied to allow splitting of slivers.

SPLITAREA: an algorithm for weighted splitting of faces in the context of a planar partition

Savino S.
Writing – Original Draft Preparation
;
2016

Abstract

Geographic data themes modelled as planar partitions are found in many GIS applications (e.g. topographic data, land cover, zoning plans, etc.). When generalizing this kind of 2D map, this specific nature has to be respected and generalization operations should be carefully designed. This paper presents a design and implementation of an algorithm to perform a split operation of faces (polygonal areas). The result of the split operation has to fit in with the topological data structure supporting variable-scale data. The algorithm, termed SPLITAREA, obtains the skeleton of a face using a constrained Delaunay triangulation. The new split operator is especially relevant in urban areas with many infrastructural objects such as roads. The contribution of this work is twofold: (1) the quality of the split operation is formally assessed by comparing the results on actual test data sets with a goal/metric we defined beforehand for the ‘balanced’ split and (2) the algorithm allows a weighted split, where different neighbours have different weights due to different compatibility. With the weighted split, the special case of unmovable boundaries is also explicitly addressed. The developed split algorithm can also be used outside the generalization context in other settings. For example, to make two cross-border data sets fit, the algorithm could be applied to allow splitting of slivers.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3508667
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