Earth Observation Systems and Pasture Modeling: A Bibliometric Trend Analysis

Abstract

An Earth observation system (EOS) is essential in monitoring and improving our understanding of how natural and managed agricultural landscapes change over time or respond to climate change and overgrazing. Such changes can be quantified using a pasture model (PM), a critical tool for monitoring changes in pastures driven by the growing population demands and climate change-related challenges and thus ensuring a sustainable food production system. This study used the bibliometric method to assess global scientific research trends in EOS and PM studies from 1979 to 2019. This study analyzed 399 published articles from the Scopus indexed database with the search term “Earth observation systems OR pasture model”. The annual growth rate of 19.76% suggests that the global research on EOS and PM has increased over time during the survey period. The average growth per article is n = 74, average total citations (ATC) = 2949 in the USA, is n = 37, ATC = 488, in China and is n = 22, ATC = 544 in Italy). These results show that the field of the study was inconsistent in terms of ATC per article during the study period. Furthermore, these results show three countries (USA, China, and Italy) ranked as the most productive countries by article publications and the Netherlands had the highest average total citations. This may suggest that these countries have strengthened research development on EOS and PM studies. However, developing counties such as Mexico, Thailand, Sri Lanka, and other African countries had a lower number of publications during the study period. Moreover, the results showed that Earth observation is fundamental in understanding PM dynamics to design targeted interventions and ensure food security. In general, the paper highlights various advances in EOS and PM studies and suggests the direction of future studies.

Characteristics of nitrogen deposition research within grassland ecosystems globally and its insight from grassland microbial community changes in China

“…The combination of these two analyses allows us to analyze the evolution of grassland nitrogen deposition research and to predict emerging themes within the discipline. Despite the comprehensive and objective nature of the analysis, bibliometric analysis and meta-analysis has been used in many studies within grassland ecosystem, such as remote sensing ( Li et al, 2021 ), soil metagenomics ( Vieira et al, 2021 ), pasture modeling ( Nduku et al, 2021 ). We used bibliometrics to analyze the responses of global nitrogen deposition to grassland ecosystems, and used a meta-analysis method to analyze the effects of nitrogen deposition on soil microbial biomass, taking China’s grassland ecosystems as an example.…”