An improved detecting information model of point annotation labelling in cartography

doi:10.11947/j.AGCS.2021.20200018

Abstract

Abstract: As one of the media of map information transmission, point annotation is an indispensable part of map. In the past, most of the researches on point annotation labelling automatically only considered confliction problem. However, they ignored the spatial distribution and structural characteristics of background features, which are closely related to point annotation quality. Therefore, we firstly construct a quantitative description of correlation between point annotation quality and background features by starting with the annotation's clarity, explicity, distribution uniformity and attribution correctness rules. Then we proposed an improved detecting information model which takes into account the detecting information caused by feature topological relation, data structure, visual position and district. We experimented the proposed method and compared with the first generation model and Maplex on national 1∶1 million geographic information data, results showed that the model could effectively decrease detecting information in local area and avoid background features maximally, then improve point annotation's clarity and Readability.

Key words: point annotation labelling, overlap structure, overlap position, detecting information model

CLC Number:

P283

HU Fengwei, QIAO Junjun, CHEN Zhangjian, GONG Lifang, LI Aiqin. An improved detecting information model of point annotation labelling in cartography[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(1): 132-141.

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