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纸质出版日期： 2022-02-07 ，
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闫凯，陈慧敏，付东杰，曾也鲁，董金玮，李世卫，吴秋生，李翰良，杜姝渊.2022.遥感云计算平台相关文献计量可视化分析.遥感学报，26（2）： 310-323
Yan K，Chen H M，Fu D J，Zeng Y L，Dong J W，Li S W，Wu Q S，Li H L and Du S Y. 2022. Bibliometric visualization analysis related to remote sensing cloud computing platforms. National Remote Sensing Bulletin， 26（2）：310-323
在遥感大数据时代背景下，遥感云计算平台的出现改变了遥感数据处理和分析的传统模式，极大地提高了运算效率，使得全球尺度的快速分析成为可能。国内外已有众多学者利用遥感云计算平台开展研究，然而相对缺乏对遥感云计算平台发展和应用的客观性综述。本文基于Web of Science（WoS）和中国知网CNKI（China National Knowledge Infrastructure）的文献数据，检索了2011-01—2021-04与遥感云计算平台相关的文献，借助文献计量方法对检索到的数据进行了发文量分析、合作分析、关键词共现分析以及文献共被引分析。结果表明：（1）国内外基于遥感云计算平台的应用研究均呈上升趋势，中国和美国是利用遥感云计算平台进行研究最活跃的国家，中国科学院是最活跃的机构；（2）相关学科交叉较为广泛，涉及遥感、环境科学与生态学、计算机科学、电子电力工程等领域，其中遥感学科是利用遥感云计算平台研究最多的领域，环境科学与生态学以及计算机科学与其他学科领域联系较密切；（3）目前谷歌地球引擎GEE（Google Earth Engine）是应用最为广泛的遥感云计算平台，此外亚马逊网络服务云（Amazon Web Services Cloud）、中科院先导地球大数据挖掘分析系统（EarthDataMiner）、PIE-Engine等平台也处于迅速发展阶段；（4）大范围的土地覆被制图、土地利用、植被变化、气候变化是遥感云平台的应用热点领域，而环境健康评估和人类活动对环境的影响研究也将成为遥感云平台未来的重要应用领域。本文研究结果定量展示了遥感云计算平台的发展历程、研究热点和应用情况，为相关研究人员把握领域发展动态并挖掘有价值的新研究方向提供了参考。
In the context of big data Remote Sensing (RS)
the development of RS cloud computing platforms has changed the mode of RS traditional data processing and analysis. It also has greatly improved the computing efficiency
which enables it to quickly analyze long-term time-series on the global scale. Although many scholars have conducted related works with RS cloud computing platforms
an objective review on the development and application of RS cloud computing platforms is still lacking. In this study
we retrieved the research literature related to RS cloud computing platforms between January 2011 and April 2021 based on the Web of Science and China National Knowledge Infrastructure. The retrieved data were analyzed in terms of publication volume
collaboration analysis
keyword co-occurrence analysis
and co-citation analysis using bibliometric methods. Results show that (1) the number of studies based on RS cloud computing platforms is increasing. China and the United States are the most active countries in this field
and the Chinese Academy of Sciences (CAS) is the most active institution. (2) The intersection of related disciplines is extensive
and it involves RS
environmental science and ecology
computer science
engineering
electrical and electronics
and other disciplines. Among them
RS is the most researched field using cloud computing platforms
and environmental science and ecology and computer science are more closely connected with other disciplinary fields. (3) At present
Google Earth Engine is a widely used RS cloud computing platform. In addition
Amazon Web Services Cloud
Earth Data Miner (a pioneering earth data mining and analysis system of CAS)
PIE-Engine
and other platforms are also in a rapid development stage. (4) Large-scale land cover mapping
land use
vegetation dynamics
and climate change have been the main application areas. Environmental health assessment and research on the impact of human activities on the environment will also be important application areas of the platforms in the future. These results quantitatively demonstrated the development history
research hotspots
and applications of RS cloud computing platforms
which provide a reference for relevant researchers to grasp the development dynamics of the field and explore valuable new research directions.
文献计量可视化遥感大数据遥感云计算平台
bibliometricvisualisationremote sensingbig dataremote sensing cloud computing platform
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