Knowledge‐Guided Automated Cartographic Generalization Process Construction: A Case Study Based on Map Analysis of Public Maps of China

IF 2.1 3区 地球科学 Q2 GEOGRAPHY
Xiaorong Gao, Haowen Yan, Zhongkui Chen, Panfei Yin
{"title":"Knowledge‐Guided Automated Cartographic Generalization Process Construction: A Case Study Based on Map Analysis of Public Maps of China","authors":"Xiaorong Gao, Haowen Yan, Zhongkui Chen, Panfei Yin","doi":"10.1111/tgis.13246","DOIUrl":null,"url":null,"abstract":"The efficacy of conveying information through maps heavily depends on the quality of map generalization. However, automating map generalization poses a complex decision‐making challenge, requiring a profound understanding of the process—specifically, knowledge about the generalization procedure. Currently, there is a scarcity of research on the sequence of generalization operations, particularly for cartographic generalization involving symbolization and labeling. On the contrary, customary maps generated in practical applications consistently adhere to the specified generalization and symbolization protocol, which makes it feasible and credible to construct this overall process based on expert knowledge. To reconcile this incongruity, this paper presents a knowledge‐guided automated cartographic generalization process construction. Firstly, an exhaustive examination of the sequential procedures involved in manual generalization and a well‐applied automated generalization system are delineated, drawing upon map analysis methodologies, observations, and expert interviews. Then, elaborate guidelines governing each phase within this process, particularly concerning the symbolization and labeling of map features, are explored. Ultimately, details of the expert interview are described and a map generalized by the well‐applied system is analyzed. The results show that the automated generalization system follows the knowledge‐guided process in this paper can significantly improve production efficiency in practice, this study serves as a connection between cartographers and developers and may help achieve a higher level of automated cartographic generalization.","PeriodicalId":47842,"journal":{"name":"Transactions in GIS","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions in GIS","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1111/tgis.13246","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 0

Abstract

The efficacy of conveying information through maps heavily depends on the quality of map generalization. However, automating map generalization poses a complex decision‐making challenge, requiring a profound understanding of the process—specifically, knowledge about the generalization procedure. Currently, there is a scarcity of research on the sequence of generalization operations, particularly for cartographic generalization involving symbolization and labeling. On the contrary, customary maps generated in practical applications consistently adhere to the specified generalization and symbolization protocol, which makes it feasible and credible to construct this overall process based on expert knowledge. To reconcile this incongruity, this paper presents a knowledge‐guided automated cartographic generalization process construction. Firstly, an exhaustive examination of the sequential procedures involved in manual generalization and a well‐applied automated generalization system are delineated, drawing upon map analysis methodologies, observations, and expert interviews. Then, elaborate guidelines governing each phase within this process, particularly concerning the symbolization and labeling of map features, are explored. Ultimately, details of the expert interview are described and a map generalized by the well‐applied system is analyzed. The results show that the automated generalization system follows the knowledge‐guided process in this paper can significantly improve production efficiency in practice, this study serves as a connection between cartographers and developers and may help achieve a higher level of automated cartographic generalization.
知识引导下的自动制图概括过程构建:基于中国公共地图分析的案例研究
通过地图传递信息的效果在很大程度上取决于地图概括的质量。然而,地图自动概括是一项复杂的决策挑战,需要对这一过程有深刻的理解,特别是对概括程序的了解。目前,有关概括操作顺序的研究还很少,尤其是涉及符号化和标注的制图概括。相反,在实际应用中生成的习惯地图始终遵循指定的概括和符号化规程,这使得基于专家知识构建这一整体流程变得可行和可信。为了解决这一矛盾,本文提出了一种知识指导下的自动制图概括流程构建方法。首先,本文借鉴地图分析方法、观察结果和专家访谈,详尽研究了人工概括和应用良好的自动概括系统所涉及的顺序步骤。然后,详细探讨了这一过程中每个阶段的指导原则,特别是关于地图特征的符号化和标记。最后,对专家访谈的细节进行了描述,并对应用良好的系统所概括的地图进行了分析。结果表明,遵循本文知识指导流程的自动概括系统在实践中能显著提高生产效率,这项研究是制图师和开发人员之间的纽带,有助于实现更高水平的自动制图概括。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Transactions in GIS
Transactions in GIS GEOGRAPHY-
CiteScore
4.60
自引率
8.30%
发文量
116
期刊介绍: Transactions in GIS is an international journal which provides a forum for high quality, original research articles, review articles, short notes and book reviews that focus on: - practical and theoretical issues influencing the development of GIS - the collection, analysis, modelling, interpretation and display of spatial data within GIS - the connections between GIS and related technologies - new GIS applications which help to solve problems affecting the natural or built environments, or business
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信