Evaluation in Generalisation

Abstract

This chapter presents the context, the issues and the research associated with the evaluation of map generalisation output as well as of map readability. Two main approaches of evaluation are described, i.e. visual and quantitative evaluation. Visual evaluation is subjective, qualitative, and time-consuming, while it is argued that quantitative evaluation is only appropriate for assessing specific aspects. Since automated evaluation is becoming very important in the field of automated generalisation, this chapter further explores the topic of automated evaluation. The previous frameworks for automated generalisation are reviewed and the three main components of automated evaluation are explained. Related to automated evaluation of generalisation output are formulas to automatically evaluate map readability. These are also discussed. This chapter ends with three case studies. The first Case study identifies and evaluates generalised building patterns. It demonstrates the three-step approach of data enrichment, data matching and constraint evaluation. The second Case study deals with formulas to automatically evaluate map readability and the third Case study carries out a comprehensive evaluation demonstrating the main aspects described in this chapter. Both visual and quantitative evaluation are applied of which the last one includes the three main components of automated evaluation. The chapter closes with conclusions and highlights research issues in evaluation.