Artículo

Bibliometric Computation Mapping Analysis of Publication Machine and Deep Learning for Food Crops Mapping using VOSviewer

Resumen

Machine learning and deep learning are currently widely used in various fields, including remote sensing for food security. However, there is no research that specifically examines the interests, developments, and trends of this research in the future. This study aims to examine the development of machine and deep learning research for mapping food crops through a bibliometric approach with computational mapping analysis using VOSviewer. Article data was obtained from the Google Scholar database using the publish or perish reference manager application. The title and abstract of the article were used to guide the search process by referring to the keyword “Machine and Deep Learning Mapping Food Crops”. 114 relevant articles were discovered. Google Scholar-indexed articles over the last ten years, from 2014 to 2023, were used as study material. The results show that machine research and deep learning for mapping food crops can be separated into three terms: machine learning, deep learning, and plant mapping. The term “Crop Mapping” has 57 links for a total of 199 links. The term “machine learning” has 41 links for a total of 79 links, and the term “deep learning” has 26 links for a total of 41 links. The results of the analysis of machine development and deep learning publications for mapping food crops in the last 10 years show a constant increase. The peak of the increase occurred in 2021 and 2022, namely 25 articles published per year, respectively. This means that this research topic is still relatively new in terms of interest and exploration, therefore there is still room further research. We examine numerous articles that have been published on machine and deep learning for crop mapping and their relation to the field studied with VOSviewer. This review can serve as a starting point for further research in different domains.
Ridwana, Riki (57209856919); Kamal, Muhammad (55266523600); Arjasakusuma, Sanjiwana (56940811200); Sugandi, Dede (56105107600); Sakti, Anjar Dimara (56943543400)
Bibliometric Computation Mapping Analysis of Publication Machine and Deep Learning for Food Crops Mapping using VOSviewer
2025
10.37934/araset.50.2.4259
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202741110&doi=10.37934%2faraset.50.2.4259&partnerID=40&md5=c8b01569374421dac3dd875d93cf68d4
Doctoral Program in Geographical Sciences, Faculty of Geography, Universitas Gadjah Mada, Yogyakarta, Indonesia; Mapping Survey and Geographic Information Study Program, Faculty of Social Sciences Education, Universitas Pendidikan Indonesia, Jl. Dr. Setiabudhi No. 229, Bandung, Indonesia; Departement of Geography Information Science, Faculty of Geography, Universitas Gadjah Mada, Bulaksumur, Yogyakarta, 55281, Indonesia; Central for Environmental Studies, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia; Remote Sensing and Geographic Information Science Research Group, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, 40132, Indonesia
All Open Access; Hybrid Gold Open Access
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