Contextual generalization of buildings in medium scale topographic maps

One of the primary goals of cartographic discipline is modeling and portraying the earth at different scales and themes to satisfy different needs. For this reason, generalization process is among popular research subjects in cartography. Especially, in recent years, both a huge upsurge in spatial data and its massive use, along with technological developments create a need to perform generalization process rapidly and automatically. In this study, it is aimed at developing some automated solutions for contextual generalization of buildings and built-up areas in deriving 1:50 000 scale maps from 1:25 000 scale maps. For that purpose, topographic data were transferred to a GIS environment. Then, contextual generalization processes for buildings and built-up areas were automatically implemented by using clustering (grouping) techniques, Delaunay triangulation and Voronoi diagrams based on generalization zones generated within blocks. All processes were automatically performed by means of BinaGEN generalization add-in, running on ArcGIS, developed by using ArcObjects Software Developer Kit and C# programming language on .NET platform, and obtained results were evaluated.