吉
斯科普斯
遥感
资源(消歧)
地理
计算机科学
数据库
环境科学
广义估计方程
机器学习
政治学
计算机网络
法学
梅德林
作者
Binh Pham‐Duc,Ho Nguyen,Hien Phan,Quan Tran-Anh
标识
DOI:10.1007/s12145-023-01035-2
摘要
Abstract Since its official establishment in 2010, Google Earth Engine (GEE) has developed rapidly and has played a significant role in the global remote sensing community. A bibliometric analysis was conducted on 1995 peer-reviewed articles related to GEE, indexed in the Scopus database up to December 2022 to investigate its trends and main applications. Our main findings are as follows: (1) The number of GEE-related articles has increased rapidly, with nearly 85% of them published in the last three years; (2) The top three domains where GEE has been extensively applied are earth and planetary sciences, environmental science, and agricultural and biological sciences. The majority of GEE-related articles were authored by scholars from China and the US, accounting for 58% of the total, with US scholars having the largest impact on the community, contributing to over 50% of the total citations; (3) Remote Sensing published the highest number of articles (26.82%), whereas Remote Sensing of Environment received the highest number of citations (30.40%); (4) The applications of GEE covered a broad range of topics, with a focus on land applications, water resource applications, climate change, and crop mapping; (5) Landsat imagery were the most popular and widely used dataset; and (6) Random forest, decision trees, support vector machines were the most commonly used machine learning algorithms in GEE. Although having a few limitations, this type of analysis should be conducted regularly to observe the development of this field on a regular basis, as the number of publications related to GEE is expected to continue to increase strongly in the coming years.
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