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Bibliometrics spatial-temporal evolution analysis of the development of remote sensing

  • role： First author第一作者
  • Affiliation：

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：huangmr@radi.ac.cn
  • Introduction：黄铭瑞，研究方向为数字地球与文献计量学。E-mail： huangmr@radi.ac.cn
HUANG Mingrui123,  
  • Affiliation：

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

JIAN Hongdeng12,  
  • Affiliation：

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 100049, China

XU Chen123,  
  • Affiliation：

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

HAO Junsheng12,  
  • Affiliation：

    Department of Academic Societies & Journals, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China

YAN Jun4,  
  • Affiliation：

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

LIU Liangyun12,  
  • Affiliation：

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

FAN Xiangtao12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

  • Email：hdguo@radi.ac.cn
  • Introduction：郭华东，研究方向为遥感科学与应用。E-mail： hdguo@radi.ac.cn
GUO Huadong12*

résumé

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.

mots-clés

remote sensing;bibliometrics;discipline development trends;research hotspot;satellite data;application fields

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