Cartographic Style Transfer: Idea, Review and Envision

被引:0
作者
Wu M. [1 ,2 ,3 ]
Sun Y. [1 ,2 ]
Lü G. [1 ,2 ,3 ]
机构
[1] College of Geographic Sciences, Nanjing Normal University, Nanjing
[2] Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing
[3] Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing
来源
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2022年 / 47卷 / 12期
基金
中国国家自然科学基金;
关键词
artificial intelligence; map design; map style; pan-map; style transfer;
D O I
10.13203/j.whugis20220439
中图分类号
学科分类号
摘要
Style transfer which originates from computer graphics has attracted broader attention in the field of cartography, considerable efforts have been made on cartographic style transfer algorithms and experimental evaluation. However, it also suffers from unclear demarcation of map style, and lack of evaluation of style transfer results. Therefore, firstly, this paper conceptually analyzes the idea of map style and the applicable scenarios of styled maps. Then, we review existing style transfer methods,and categorize available style transfer methods into three groups and compare them with details: Probability statistics-based, content-based, and neural network-based. We also discuss three major types of map style transfer methods: Image to map, remote sensing imagery to map, and image to relief shading. And we compare the advantages and disadvantages of style transfer with vector and raster maps. Finally, we envision the future research of map style transfer in terms of three possible research questions: How to select reference images, how to evaluate style transfer results, and how to integrate style transfer into map design process. © 2022 Wuhan University. All rights reserved.
引用
收藏
页码:2069 / 2084
页数:15
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