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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2023, Vol. 20, No. 5, pp. 319-326

Using natural language processing techniques to analyze the use of Google Earth Engine in 2015–2023 remote sensing research publications

A.B. Jaxylykova 1 , A.M. Mirash 2 , A.A. Pak 1 , Armanovich Ziyaden 1 
1 Institute of Information and Computational Technologies, Almaty, Kazakhstan
2 BL-group, Almaty, Kazakhstan
Accepted: 10.10.2023
DOI: 10.21046/2070-7401-2023-20-5-319-326
Remote sensing is of key importance for the sustainable development of human activities. Previously, the field of satellite data processing was dominated by specialized professional packages with high costs. With the expansion of information technology capabilities, the landscape of this field has undergone a significant transformation due to the emergence and development of cloud-based technologies that combine built-in access to satellite databases with tools for their processing. The best known in this area is the Google Earth Engine (GEE) product, which first appeared in 2010. Currently, this product from Google has become a serious competitor to expensive professional satellite data processing packages, which often have a less intuitive interface, due to limited audience and financial barriers. GEE provides users with free (with certain limits on the amount of data transferred) access to most satellite databases, as well as cloud-based tools for processing them. In addition, it should be noted that GEE has opened new horizons for detailed monitoring of the environment and climate change. Its ability to process large volumes of global remote sensing data and automate the analysis of satellite imagery has opened revolutionary opportunities for users to work towards analyzing the spectral properties of the Earth’s underlying surface. The frequency of GEE use and its temporal dynamics can serve as an indicator of the potential development of remote sensing processing in different countries and in different scientific directions. The aim of this paper is to analyze the trends of GEE frequency in scientific and technical publications in the period 2015–2023 based on natural language processing techniques. The findings show a power growth in the frequency of GEE mentions in the abstracts of scientific articles between 2015 and 2022. Moreover, the dominant use of GEE is recorded in papers by authors affiliated with the PRC Academy of Sciences. Authors from US universities lose out by more than a factor of two. This situation diagnoses the outstripping growth of PRC scientific research and displacement of US scientific institutions from the leading positions in the world in the field of remote sensing.
Keywords: remote sensing, satellite databases, cloud processing technologies, Google Earth Engine, content analysis, longitudinal analysis
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