No abstract

The generation of maps in real-time web-services introduces challenges concerning map legibility. As these services lack the important input of a traditional cartographer, analytical measures of the legibility are called for. The aim of this study was to develop such legibility measures, and to evaluate them with the help of expert users. Measures of the amount of information, spatial distribution and object complexity were developed and evaluated. The results indicated that some of the measures could be used to describe map legibility.

Readability is a major issue with all maps. In this study, we evaluated whether we can predict map readability using analytical measures, both single measures and composites of measures. A user test was conducted regarding the perceived readability of a number of test map samples. Evaluations were then performed to determine how well single measures and composites of measures could describe the map readability. The evaluation of single measures showed that the amount of information was most important, followed by the spatial distribution of information. The measures of object complexity and graphical resolution were not useful for explaining the map readability of our test data. The evaluations of composites of measures included three methods: threshold evaluation, multiple linear regression and support vector machine. We found that the use of composites of measures was better for describing map readability than single measures, but we could not identify any major differences in the results of the three composite methods. The results of this study can be used to recommend readability measures for triggering and controlling the map generalization process of online maps.