Bibliometrics spatial-temporal evolution analysis of the development of remote sensing
- Vol. 27, Issue 11, Pages: 2449-2466(2023)
Published： 07 November 2023
DOI： 10.11834/jrs.20232659
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摘要
遥感已成为支撑国家资源能源调查、粮食安全监测、生态环境保护、自然灾害评估、国防安全等的重要信息源。利用文献计量学方法定量分析遥感相关文献所承载知识的时空分布、数量关系和变化规律，梳理并提取遥感学科发展趋势及研究热点的时空演化特征，可为遥感学科的建设与发展提供重要科学支撑。对1962年—2021年间发表并被SCI数据库收录的遥感相关文章进行文献计量研究，对比分析了国内外典型遥感卫星的文献发表及应用情况，系统剖析了1962年—2021年美国、欧洲、中国遥感研究热点及其变化过程，总结了美国、欧洲、中国学者在合成孔径雷达（SAR）、高光谱（Hyperspectral）及激光雷达（LiDAR）3大遥感前沿技术的研究特点。结果表明：（1）遥感学科SCI文章数自1998年起呈现快速增长、加速增长的趋势。1962年—2012年全球累积发表遥感相关SCI文章69666篇，2013年—2021年全球累积发文100131篇。2014年，中国（第一作者）年度发表遥感相关SCI文章2048篇，首次超过美国（第一作者）年度1454篇跃居全球第一，此后一直领先。2021年，中国（第一作者）年度发表遥感相关SCI文章8063篇，占全球该年度遥感相关SCI文章19121篇的42.17%；（2）在遥感技术方面，卫星遥感平台从单一卫星向专业小卫星、卫星星座方向发展；卫星传感器从全色、单波段起步，逐步向SAR、高光谱、LiDAR等前沿技术快速发展；（3）在遥感数据应用方面，Landsat、MODIS、Sentinel等国外数据自出现以来就一直被全球用户广泛使用，尤其是中国学者的遥感应用研究高度依赖这些国外卫星数据，近年来国产卫星的应用呈快速发展趋势；（4）当前中外遥感科学研究热点差异显著：美国遥感学者依托Landsat、MODIS、激光雷达等先进卫星和载荷技术，遥感已广泛深入各应用领域；欧洲遥感学者十分重视Sentinel系列卫星的科学研究和应用；中国遥感研究在所有领域和卫星应用方面都表现了突出的数量优势，且中国遥感学者更关注SAR、高光谱、LiDAR以及深度学习、神经网络、特征提取等前沿技术与算法研究。
Abstract
Remote Sensing (RS) has become an essential information source for national resource and energy surveys
food security monitoring
ecological environmental protection
natural disaster assessment
and national defense security. Bibliometric is a helpful method to analyze the development dynamics
hotspots
and evolution in the RS discipline. It is a powerful approach to sort out and visualize the progress of RS development.
This study conducts a bibliometric analysis of RS-related Science Citation Index (SCI) papers published from 1962 to 2021. The research hotspots and changes of RS in the United States
Europe
and China from 1962 to 2021 are systematically determined. The application of typical RS satellites globally and in China are compared and analyzed. The research characteristics of US
European
and Chinese scholars in the three frontier technologies (i.e.
Synthetic Aperture Radar
Hyperspectral
and LiDAR) are summarized.
Results show that (1) the number of SCI papers and authors in RS has shown a trend of rapid growth and accelerated growth since 1998
from 69
666 published in 2012 to 169
797 in 2021. China has surpassed the US in its annual publication to become the first since 2014
and it has been far ahead since then. It published 8
063 RS SCI papers by 2021
which accounted for 42.17% of the 19
121 global publications. (2) In terms of RS technology
RS started from multispectral imaging
and it developed rapidly to the frontier technologies of synthetic aperture radar
hyperspectral
LiDAR
unmanned aerial vehicle (UAV)
high-resolution image
and deep learning. Furthermore
RS gradually played an increasingly important role in many application fields. (3) In terms of RS data application
Landsat
MODIS
Sentinel
and other foreign data have been widely used by global users. Chinese scholars highly rely on these foreign satellite data to conduct RS research. By contrast
the application of domestic satellites is relatively rare
and the international influence of domestic satellites is very weak
which is very mismatched with China’s status of RS. (4) Significant differences are observed in the hotspots of RS research between China and other countries. By relying on advanced satellite and payload technologies (e.g.
Landsat and MODIS)
the US developed science- and demand-driven RS research
which has been widely used in various application fields. European RS scholars attached great importance to the research and application of Sentinel satellites
which have surpassed Landsat in the number of SCI papers they published. Chinese RS has shown outstanding quantitative advantages in all research fields and applications. Meanwhile
Chinese RS scholars pay more attention to synthetic aperture radar
hyperspectral
LiDAR
deep learning
neural networks
feature extraction
and other cutting-edge technologies and algorithms.
关键词
遥感文献计量学科发展趋势研究热点卫星数据应用领域
Keywords
remote sensingbibliometricsdiscipline development trendsresearch hotspotsatellite dataapplication fields
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State Key Laboratory of Remote Sensing Science, Beijing Normal University
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