Bibliometric visualization analysis related to remote sensing cloud computing platforms

Abstract

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.