Proceedings of the Spatial Science Institute Biennial International Conference (SSC2007), Hobart, Tasmania, Australia, 14-18 May 2007 (non-refereed paper) 537 AN INTERNATIONAL RESEARCH SURVEY: CARTOGRAPHIC GENERALISATION PRACTICES AT MAPPING AGENCIES * Sharon Kazemi, Samsung Lim and Linlin Ge School of Surveying and Spatial Information Systems The University of New South Wales, Sydney NSW 2052, Australia s.kazemi@student.unsw.edu.au ABSTRACT This paper aims to report on the knowledge acquisition process of cartographic practices by undertaking a cartographic generalisation survey. From November 2005 to May 2006, a survey of cartographic generalisation practices was conducted at several national mapping agencies, state mapping agencies and a number of software vendors, in order to capture the cartographers’ knowledge about the principles of cartographic generalisation and their experience with existing generalisation software. The survey was designed to collect experts’ recommendations in relation to new technologies and the future generalisation research that could be undertaken by universities and the spatial information industry. The survey results are being utilised to build a knowledge- based expert system on feature generalisation. Cartographers’ feedback was provided in the form of broad qualitative statements and was analysed to obtain the most pertinent comments. Statistical responses were assessed in quantitative terms. This paper provides key findings from the analysis of the survey results. The outcome of this research is the development of a conceptual framework to generalise spatial databases and a practical realisation of the framework in order to deliver coherent capabilities and automate the generalisation of features as much as possible for “derivative mapping” applications. INTRODUCTION International Cartographic Association (1973) defined cartographic generalization as a process of selection and simplified representation of detail appropriate to scale and/or purpose of a map. Weibel and Dutton (1999) noted, “Generalization means a process which realise transition between different models representing a portion of the real world at decreasing detail, while maximizing information content with respect to a given application”. For the automation of the map generalization process, it is necessary to integrate cartographers' experience with the generalization operations within Geographical Information Systems (GIS). Cartographic knowledge can be compiled through expert opinion using survey methods that is a form of data mining and knowledge discovery. Knowledge discovery has lead to the amassing of very large repositories of customer, operations, scientific, and other types of data using a number of techniques such as predictive modelling (Provost and Kolluri 1999). Survey research in general aims to * This paper was prepared during the first author’s visiting scholar appointment (30 August 2007 – 25 January 2007) at the Geographic Information Science Center, College of Environmental Design of the University of California, Berkeley, CA 94720-1820 USA.