A bibliometric analysis of semantic segmentation in remote sensing images from 1981 to 2024

Yangjie Lin

doi:10.54254/2977-3903/9/2024092

Research Article

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Published on 31 July 2024

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Lin,Y. (2024). A bibliometric analysis of semantic segmentation in remote sensing images from 1981 to 2024. Advances in Engineering Innovation,9,34-41.

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A bibliometric analysis of semantic segmentation in remote sensing images from 1981 to 2024

Yangjie Lin *^,1,

¹ Wuhan University

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2977-3903/9/2024092

Abstract

Semantic segmentation of remote sensing images plays a crucial role in various fields, such as disaster assessment, forestry measurement, and environmental monitoring. This study conducts a bibliometric analysis to investigate the research trends and development of semantic segmentation in remote sensing from 1981 to 2024. Utilizing the Web of Science Core Collection database, we retrieved representative literature data and analyzed the publication trends, main source journals, institutional cooperation, and keyword co-occurrence networks. The results show that the number of publications in this field has increased significantly since 2000, with an exponential growth pattern. Remote sensing is the most active research topic, followed by imaging science, photographic technology, and electrical and electronic engineering. The analysis of institutional cooperation reveals that Chinese research institutions, such as the Chinese Academy of Sciences and Wuhan University, play a leading role in this field and maintain close collaboration with research institutions worldwide. The keyword co-occurrence network analysis demonstrates the evolution of research focus from basic remote sensing and image processing techniques in the early stage to advanced image processing algorithms in the middle stage and deep learning and neural network technologies in the recent stage. The findings provide valuable insights into the current status and future trends of semantic segmentation in remote sensing, highlighting the importance of international cooperation and interdisciplinary exchange in driving technological innovation.

Keywords

remote sensing, semantic segmentation, bibliometric analysis, research trends, international cooperation, interdisciplinary research

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Cite this article

Lin,Y. (2024). A bibliometric analysis of semantic segmentation in remote sensing images from 1981 to 2024. Advances in Engineering Innovation,9,34-41.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Journal：Advances in Engineering Innovation

Volume number: Vol.9

ISSN：2977-3903(Print) / 2977-3911(Online)

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