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Generalisation Operators

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References

2000Quantitative geography : perspectives on spatial data analysis968 cited
1966The Principles of Selection264 cited
2010A Road Network Selection Process Based on Data Enrichment and Structure Detection120 cited
2005Variable-scale Topological Data Structures Suitable for Progressive Data Transfer: The GAP-face Tree and GAP-edge Forest98 cited
2002Detecting Building Alignments for Generalisation Purposes79 cited
1992Models and Experiments for Adaptive Computer-Assisted Terrain Generalization76 cited
2007Relations among Map Objects in Cartographic Generalization74 cited
2009Selective omission of road features based on mesh density for automatic map generalization73 cited
2007A synoptic View of Generalisation Operators67 cited
2007Automatic identification of urban settlement boundaries for multiple representation databases62 cited
2013Scaling of Geographic Space as a Universal Rule for Map Generalization61 cited
2009Feature pruning by upstream drainage area to support automated generalization of the United States National Hydrography Dataset61 cited
2007Conceptual Models of Generalisation and Multiple Representation59 cited
2012Integration of linear and areal hierarchies for continuous multi-scale representation of road networks57 cited

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2011A typology of operators for maintaining legible map designs at multiple scales55 cited

1991Expert Systems in Cartographic Design55 cited

Cited by

2019CartAGen: an Open Source Research Platform for Map Generalization19 cited
2023Using machine learning and data enrichment in the selection of roads for small-scale maps18 cited
2022Building simplification of vector maps using graph convolutional neural networks11 cited
2023Polyline simplification using a region proposal network integrating raster and vector features10 cited
2023DeepMapScaler: a workflow of deep neural networks for the generation of generalised maps9 cited
2021Scale-Dependent Point Selection Methods for Web Maps8 cited
2020Verifying and Exploring Settlement Selection Rules and Variables for Small‐Scale Maps Using Decision Tree‐Based Models7 cited
2021MSLF: multi-scale legibility function to estimate the legible scale of individual line features5 cited