The process of performing cartographic generalization in an automatic way applied on geographic information is of highly interest in the field of cartography, both in academia and industry. Many research e↵orts have been done to implement di↵erent automatic generalization approaches. Being able to answer the research question on automatic generalization, another interesting question opens up: ”Is it possible to retrieve and visualize geographic information in any arbitrary scale?” This is the question in the field of vario-scale geoinformation. Potential research works should answer this question with solutions which provide valid and efficient representation of geoinformation in any on-demand scale. More brilliant solutions will also provide smooth transitions between these on-demand arbitrary scales. Space-Scale-Cube (Meijers and Van Oosterom 2011) is a reactive tree (Van Oosterom 1991) data structure which shows positive potential for achieving smooth automatic vario-scale generalization of area features. The topic of this research work is investigation of adaptation of this approach on an interesting class of geographic information: road networks datasets. Firstly theoretical background will be introduced and discussed and afterwards, implementing the adaptation would be described. This research work includes development of a hierarchical data structure based on road network datasets and the potential use of this data structure in vario-scale geoinformation retrieval and visualization.

The process of performing cartographic generalization in an automatic way applied on geographic information is of highly interest in the field of cartography, both in academia and industry. Many research e↵orts have been done to implement di↵erent automatic generalization approaches. Being able to answer the research question on automatic generalization, another interesting question opens up: ”Is it possible to retrieve and visualize geographic information in any arbitrary scale?” This is the question in the field of vario-scale geoinformation. Potential research works should answer this question with solutions which provide valid and efficient representation of geoinformation in any on-demand scale. More brilliant solutions will also provide smooth transitions between these on-demand arbitrary scales. Space-Scale-Cube (Meijers and Van Oosterom 2011) is a reactive tree (Van Oosterom 1991) data structure which shows positive potential for achieving smooth automatic vario-scale generalization of area features. The topic of this research work is investigation of adaptation of this approach on an interesting class of geographic information: road networks datasets. Firstly theoretical background will be introduced and discussed and afterwards, implementing the adaptation would be described. This research work includes development of a hierarchical data structure based on road network datasets and the potential use of this data structure in vario-scale geoinformation retrieval and visualization.:Declaration of Authorship i Abstract iii Acknowledgements iv List of Figures vii Abbreviations viii 1 Introduction 1 1.1 Problem Definition 2 1.1.1 Research Questions 2 1.1.2 Objectives 3 1.2 Proposed Solution 3 1.3 Structure of the Thesis 4 1.4 Notes on Terminology 4 2 Cartographic Generalization 6 2.1 Cartographic Generalization: Definitions and Classifications 6 2.2 Generalization Operators 9 2.3 Efforts on Vario-Scale Visualization of Geoinformation 10 2.4 Efforts on Generalization of Road Networks and Similar Other Networks 16 2.4.1 Geometric Generalization of Networks 17 2.4.2 Model Generalization of Networks 18 2.5 Clarification of Interest 20 3 Theory of Road Network SSC 21 3.1 Background of an SSC 21 3.1.1 tGAP 21 3.1.2 Smoothing tGAP 23 3.2 Road Network as a ’Network’ 24 3.2.1 Short Background on Graph Theory 5 3.3 Formation of Road Network SSC 26 3.3.1 Geometry 26 3.3.2 Network Topology 27 3.3.3 Building up tGAP on The Road Network 28 3.3.4 Smoothing of Road Network SSC 31 3.3.4.1 Smoothing Elimination 32 3.3.4.2 Smoothing Simplification 32 3.4 Reading from a road network SSC 34 3.4.1 Discussion on Scale 34 3.4.2 Iterating Over The Forest 35 3.4.3 Planar Slices 35 3.4.4 Non-Planar Slices 36 4 Implementation of Road Network SSC 37 4.1 General Information Regarding The Implementation 37 4.1.1 Programming Language 37 4.1.2 RDBMS 38 4.1.3 Geometry Library 39 4.1.4 Graph Library 39 4.2 Data Structure 40 4.2.1 Node 40 4.2.2 Edge 41 4.2.3 Edge-Node-Relation 41 4.3 Software Architecture 42 4.3.1 More Detail on Building The SSC 42 4.3.1.1 Initial Data Processing 42 4.3.1.2 Network Processing 43 4.3.2 More Detail on Querying The SSC 46 4.3.2.1 Database Query 46 4.3.2.2 Building Geometry 46 4.3.2.3 Interface and Visualization 47 4.4 Results 48 5 Conclusions and Outlook 49 Bibliography 51