Bibliometric and social network analysis on the use of satellite imagery in agriculture: an entropy-based approach
Riccardo Dainelli, Fabio Saracco

TL;DR
This study analyzes the structure and societal reach of satellite imagery research in agriculture using bibliometric and social network methods, revealing key research trends and a communication gap with the public.
Contribution
It combines bibliometric and social network analysis to map research trends and public engagement in satellite imagery for agriculture, highlighting gaps in academic-public communication.
Findings
USA and China are the leading countries in research output.
Key research topics include resolution, Landsat, yield, wheat, and multispectral imaging.
Minimal academic engagement on Twitter, mostly private company advertising.
Abstract
Satellite imagery is gaining popularity as a valuable tool to lower the impact on natural resources and increase profits for farmers. The purpose of this study is twofold: to mine the scientific literature to reveal the structure of this research domain, and to investigate to what extent scientific results can reach a wider public audience. To meet these two objectives, a Web of Science and a Twitter dataset were retrieved and analysed, respectively. For the academic literature, different performances of various countries were observed: the USA and China resulted as the leading actors, both in terms of published papers and employed researchers. Among the categorised keywords, "resolution", "Landsat", "yield", "wheat" and "multispectral" are the most used. Then, analysing the semantic network of the words used in the various abstracts, the different facets of the research in satellite…
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Taxonomy
TopicsEconomic and Technological Innovation · Global Trade and Competitiveness
