Generalisation in Practice Within National Mapping Agencies

National Mapping Agencies (NMAs) are still among the main end users of research into automated generalisation, which is transferred into their production lines via various means. This chapter includes contributions from seven NMAs, illustrating how automated generalisation is used in practice within their partly or fully automated databases and maps production lines, what results are currently being obtained and what further developments are on-going or planned. A contribution by the European Joint Research Center reports on the use of multiple representation and generalisation in the context of the implementation of the European INSPIRE directive. The chapter finishes with a synthesis of recent achievements, as well as future challenges that NMAs have begun to tackle.

[1]  Julien Gaffuri,et al.  Toward Web Mapping with Vector Data , 2012, GIScience.

[2]  M. Pla,et al.  An example of database generalization workflow: the Topographic Database of Catalonia at 1:25.000 , 2003 .

[3]  Robert Weibel,et al.  Generalising spatial data and dealing with multiple representations , 1999 .

[4]  Production of a national 1:1,000,000-scale hydrography dataset for the United States: feature selection, simplification, and refinement , 2009 .

[5]  W. A. Mackaness,et al.  Rural and Urban Road Network Generalization Deriving 1:250,000 From 1:1250: International Cartographic Conference, A Coruna , 2005 .

[6]  A. Ruas Modèle de généralisation de données géographiques à base de contraintes et d'autonomie , 1999 .

[7]  Jantien Stoter,et al.  Specifying Map Requirements for Automated Generalization of Topographic Data , 2009 .

[8]  Annabelle Boffet,et al.  URBAN CLASSIFICATION FOR GENERALIZATION ORCHESTRATION , 2000 .

[9]  Bernhard Jenny,et al.  Scree Representation on Topographic Maps , 2010 .

[10]  William Mackaness,et al.  Rural and Urban Road Network Generalization Deriving 1:250,000 From 1:1250 , 2005 .

[11]  Jean-Claude Müller,et al.  Line Generalization Based on Analysis of Shape Characteristics , 1998 .

[12]  Robert Weibel,et al.  Integrating multi agent, object oriented and algorithmic techniques for improved automoated map generalisation , 2001 .

[13]  Spot heights generalization: deriving the relief of theTopographic Database of Catalonia at 1:25,000 from the master database , 2007 .

[14]  L. Sugarbaker,et al.  The National Map , 2011 .

[15]  W. Mackaness,et al.  10th ICA Workshop on Generalisation and Multiple Representation , 2007 .

[16]  Monika Sester,et al.  Web Generalisation Service in GiMoDig – towards a standardised service for real-time generalisation , 2005 .

[17]  Generalizing the altimetric information of the Topographic Database of Catalonia at 1:5,000: classification and selection of break lines , 2011 .

[18]  Barbara P. Buttenfield,et al.  Adapting Generalization Tools to Physiographic Diversity for the United States National Hydrography Dataset , 2011 .

[19]  Sidonie Christophe Cartographic Styles between traditional and original (towards a cartographic style model) , 2012 .

[20]  Maria Pla,et al.  ICC Topographic Databases: Design of a MRDB for data management optimization , 2012 .

[21]  Sheng Zhou,et al.  Shape-Aware Line Generalisation With Weighted Effective Area , 2004, SDH.

[22]  Menno-Jan Kraak,et al.  Challenges for Automated Generalisation at European Mapping Agencies: A Qualitative and Quantitative Analysis , 2010 .

[23]  Stuart Thom A Strategy for Collapsing OS Integrated Transport Network™ dual carriageways. , 2005 .

[24]  Guillaume Touya,et al.  Quality Assessment of the French OpenStreetMap Dataset , 2010, Trans. GIS.

[25]  Guillaume Touya,et al.  EuroSDR research on state-of-the-art of automated generalisation on commercial software : Main findings and conclusions , 2010 .

[26]  Sylvain Bard,et al.  Quality Assessment of Cartographic Generalisation , 2004, Trans. GIS.

[27]  François Lecordix,et al.  Managing Generalisation Updates in IGN Map Production , 2007 .

[28]  R. Böhme International cartographic conference: 6–13 August 1984, Perth, Australia , 1985 .

[29]  Dirk Burghardt,et al.  Workflow management and generalisation services , 2006 .

[30]  Stuart Thom Automatic Resolution of Road Network Conflicts using Displacement Algorithms Orchestrated by Geographical Agents , 2007 .

[31]  Corinne Plazanet,et al.  A Platform for Research in Generalization: Application to Caricature , 1997, GeoInformatica.

[32]  Regnauld Nicolas,et al.  Deriving Products from a Multi Resolution Database using Automated Generalisation at Ordnance Survey , 2013 .

[33]  J. E. Stoter,et al.  Generalisation within NMA's in the 21st century , 2005 .

[34]  Barbara P. Buttenfield,et al.  Hydrographic Generalization Tailored to Dry Mountainous Regions , 2011 .

[35]  Barbara P. Buttenfield,et al.  Mastering map scale: balancing workloads using display and geometry change in multi-scale mapping , 2010, GeoInformatica.

[36]  Jantien Stoter,et al.  Fully automated generalization of a 1:50k map from 1:10k data , 2014 .

[37]  Kusay Jaara,et al.  Extraction of Cartographic Contour Lines Using Digital Terrain Model (DTM) , 2011 .

[38]  Arnaud Le Bris,et al.  Cartography of High Mountain Areas Testing of a New Digital Cliff Drawing Method , 2008 .

[39]  Barbara P. Buttenfield,et al.  Automated thinning of road networks and road labels for multiscale design of The National Map of the United States , 2013 .

[40]  Sidonie Christophe,et al.  Creative Colours Specification Based on Knowledge (COLorLEGend system) , 2011 .

[41]  Jantien Stoter,et al.  Fully automated generalisation of topographic data in current geo-information environments , 2011 .

[42]  Jantien E. Stoter,et al.  Methodology for evaluating automated map generalization in commercial software , 2009, Computers, Environment and Urban Systems.

[43]  F. Töpfer,et al.  The Principles of Selection , 1966 .

[44]  Massimo Rumor Urban and Regional Data Management: UDMS Annual 2011 , 2011 .

[45]  Robert Weibel,et al.  Improving Automated Generalisation for On- Demand Web Mapping by Multiscale Databases , 2002 .

[46]  Stefano Spaccapietra,et al.  Modelling geographic data with multiple representations , 2004, Int. J. Geogr. Inf. Sci..

[47]  Chris Anderson-Tarver,et al.  Automated Centerline Delineation to Enrich the National Hydrography Dataset , 2012, GIScience.

[48]  Anne Ruas,et al.  Modèle de généralisation de données urbaines à base de contraintes et d´autonomie Urban data generalization models using constraints and autonomy , 1999 .

[49]  L. Stanislawski,et al.  Pruning of Hydrographic Networks: A Comparison of Two Approaches , 2011 .

[50]  R. Thomson,et al.  The ‘ Good Continuation ’ Principle of Perceptual Organization applied to the Generalization of Road Networks , 2002 .

[51]  Guillaume Touya,et al.  State-of-the-art of automated generalisation in commercial software , 2010 .

[52]  Jahard THE IMPLEMENTATION OF NEW TECHNOLOGY TO AUTOMATE MAP GENERALISATION AND INCREMENTAL UPDATING PROCESSES , 2003 .