Monitoring And Assessing Wetlands Using Google Earth Engine: A Bibliometric Review (2017–2024)

Abstract

This study presents a comprehensive bibliometric analysis of research papers focusing on wetland monitoring and assessment using Google Earth Engine (GEE) from 2017 to 2024. The analysis examined 308 publications from Scopus, revealing significant trends in publication patterns, geographic distribution, methodological approaches, and research impact. Results show a dramatic increase in publications since 2017, with peak growth occurring between 2022-2024. China emerged as the leading contributor (43% of publications), followed by the United States (20%) and Canada (10%). The analysis identified Earth and Planetary Sciences (27.7%) and Environmental Science (21.9%) as dominant subject areas. Remote Sensing emerged as the primary publication venue with 78 papers and 2,121 citations. The study revealed strong international collaboration networks among 56 key scholars, with Random Forest emerging as the most widely adopted classification method. The research highlighted significant advances in integrating multi-source data and machine learning techniques for wetland monitoring, while also identifying gaps in socio-ecological research and biodiversity monitoring. This analysis provides valuable insights into the evolution of GEE-based wetland research and suggests future directions for advancing the field.