Cartography and Neural Networks: A Scientometric Analysis Based on CiteSpace

Propelled by emerging technologies such as artificial intelligence and deep learning, the essence and scope of cartography have significantly expanded. The rapid progress in neuroscience has raised high expectations for related disciplines, furnishing theoretical support for revealing and deepening...

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Bibliographic Details
Published inISPRS international journal of geo-information Vol. 13; no. 6; p. 178
Main Authors Cheng, Shiyuan, Zhang, Jianchen, Wang, Guangxia, Zhou, Zheng, Du, Jin, Wang, Lijun, Li, Ning, Wang, Jiayao
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.06.2024
Subjects
Analysis
Artificial intelligence
Cartography
CiteSpace
Cluster analysis
Clusters
Cognitive models
Deep learning
Evolution
Interdisciplinary research
knowledge mapping
Machine learning
Mapping
Multidisciplinary research
neural network
Neural networks
Neurosciences
Science
Trends
visual analysis
China
Germany
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Summary:Propelled by emerging technologies such as artificial intelligence and deep learning, the essence and scope of cartography have significantly expanded. The rapid progress in neuroscience has raised high expectations for related disciplines, furnishing theoretical support for revealing and deepening the essence of maps. In this study, CiteSpace was used to examine the confluence of cartography and neural networks over the past decade (2013–2023), thus revealing the prevailing research trends and cutting-edge investigations in the field of machine learning and its application in mapping. In addition, this analysis included the systematic categorization of knowledge clusters arising from the fusion of cartography and neural networks, which was followed by the discernment of pivotal clusters in the field of knowledge mapping. Crucially, this study diligently identified the critical studies (milestones) that have made significant contributions to the development of these elucidated clusters. Timeline analysis was used to track these studies’ origins, evolution, and current status. Finally, we constructed collaborative networks among the contributing authors, journals, institutions, and countries. This mapping aids in identifying and visualizing the primary contributing factors of the evolution of knowledge mapping encompassing cartography and neural networks, thus facilitating interdisciplinary and multidisciplinary research and investigations.
ISSN:2220-9964
2220-9964
DOI:10.3390/ijgi13060178