Spatial generalization in sketch maps: A systematic classification

Sketch maps are one of the most commonly used instruments to study people's perception of the environment. While previous research has focused on analyzing sketch maps with respect to their accuracy, completeness, or distortion, there is little study focusing on generalization (the level of geometric details of the depicted features) in sketch maps. Furthermore, when investigating people's mental representations of space, researchers compute the accuracy or completeness of sketch maps via a one-to-one comparison of sketched features with features in metric map data. The task of one-to-one comparison becomes problematic because features in sketch map often represent many features in a metric map. This paper identifies the frequently occurring generalizations in 108 sketch maps of small urban area by manually extracting generalized features such as streets and buildings and classifying them based on similarities. We found three generalization types in streets, two in junctions and four in buildings. To evaluate our classification, we created 10 sketch maps by systematically introducing the nine identified generalizations. A study was conducted wherein five raters were briefed about the different general-ization types. Each of them classified the features in sketch maps as generalized and non-generalized. We found a high inter-rater agreement, implying the comprehensibility and clarity of the identified generalization types. We propose that such systematic view on the generalization in sketch maps would standardize the process of comparing them with metric map data as well as enable a new way of analyzing sketch maps with respect to generalization.

Automated summary

Sketch maps are widely used in studying people's perception of the environment, but research on generalization in these maps is limited. This paper identifies and classifies frequently occurring generalizations in 108 sketch maps of a small urban area. The study also evaluates the classification through inter-rater agreement, suggesting the comprehensibility and clarity of the identified generalization types. The findings provide a systematic view on the generalization in sketch maps and offer a new way of analyzing them.