Understanding the usage of land use and land cover classifiers in scientific research

Authors

DOI:

https://doi.org/10.32358/rpd.2023.v9.660

Keywords:

land use and land cover, classification, bibliometrics

Abstract

Purpose: assess the primary methods utilized in land use and land cover classification research to determine the most frequently applied techniques and potential trends Methodology/Approach: a bibliometric study was carried out in the Scopus scientific article databases, counting the use of classification methods between 2012 and 2022. The obtained data was converted into SQL database tables and processed using queries, looking for articles whose abstracts contains keywords related to land cover and land use methods. Findings: a general growth trend in the studies of this area was discovered, with an increase in the use of machine learning-based methodologies and stabilization in the use of other methods. Statistical methods were also heavily used, while others were used less frequently. Research Limitation/implication: it’s important to note that keywords present in abstract sections does not necessarily correspond to the mentioned methods being applied in the studies. This leads to some expected degree of imprecision, but the data remains a reasonable representation of the popularity of each method. Originality/Value of paper: considering that the scientific literature lacks a quantitative understanding of the usage of land use and land cover classifiers, this work aims to fill that gap by providing usable data.

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Author Biographies

Vitor da Silva Gonçalves, Universidade Candido Mendes

Master in Operational Research and Computational Intelligence.

Italo de Oliveira Matias, Universidade Candido Mendes University

Graduated in Computer Science from the Federal University of Paraíba (1998). Master's degree from COPPE/UFRJ (2001) in Systems and Computer Engineering in the area of Computer Graphics. PhD from COPPE/UFRJ (2007) in Civil Engineering in the area of Computer Systems/Computational Intelligence. Post-Doctorate in Engineering and Materials Sciences from Universidade Norte-Fluminense (2011). He is a professor at UCAM (Campos dos Goytacazes) where he teaches and supervises the POIC master's degree and the doctorate in Regional Planning and City Management. He works in the areas: Artificial Intelligence, Data Science, Big Data, Digital Image Processing, Geoprocessing, Computer Vision and Emerging Digital Technologies.

Aldo Shimoya, Candido Mendes University

Aldo Shimoya has a degree in Agronomy from the Federal University of Mato Grosso (1982), a master's degree (1987) and a doctorate (2000) in Genetics and Breeding from the Federal University of Viçosa. Professor at Universidade Candido Mendes, in undergraduate courses in Production, Civil and Mechanical Engineering; in the master's degree in Operational Research and Computational Intelligence; and master's and doctorate degrees in Regional Planning and City Management.

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Published

2023-12-29

How to Cite

Gonçalves, V. da S., Matias, I. de O., & Shimoya, A. (2023). Understanding the usage of land use and land cover classifiers in scientific research. Revista Produção E Desenvolvimento, 9(1), e660. https://doi.org/10.32358/rpd.2023.v9.660

Issue

Vol. 9 No. 1 (2023): January-December

Section

Bibliometric and scientometric studies

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