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Remote sensing applied to cocoa crop identification, a thematic review

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 15 No. 5 (2025)

DOI
10.11591/ijece.v15i5.pp4848-4855
ISSN
2722-2578, 2088-8708
Published
2025-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

This article presents a thematic review of 25 publications related to the use of remote sensing techniques for the identification of cocoa crops from 2000 to 2023. Although the use of remote sensing techniques is widely used for mapping different covers because it is very useful in discriminating them, the generation of maps of cocoa crops presents challenges due to their spectral behavior similar to that of forests. This is because cocoa cultivation, being an agroforestry system that is developed in association with timber trees, causes the classification algorithms used to fail to differentiate between forest cover and cocoa crops. For this reason, this study seeks to investigate the different remote sensing techniques used in the mapping of cocoa crops, as well as an analysis of the structure of the publications highlighting the connections between countries and the factors that motivated the authors to research this crop.

Collaboration network of the authors

9 authors · 17 co-authorship links · 10 across different organisations

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  • Universidad Católica de Manizales
  • Universidad Nacional de Colombia
  • Universidad de Manizales
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Yeison Alberto Garcés-GómezUniversidad Católica de Manizales5
LUIS FERNANDO DIAZ CADAVIDUniversidad Nacional de Colombia1
Fredy E. HoyosUniversidad Nacional de Colombia1
Alejandro RincónUniversidad Católica de Manizales1
Gloria Yaneth Flórez YépesUniversidad Católica de Manizales1
Juan Carlos Granobles ToresUniversidad de Manizales1
María Nancy Marín OlayaUniversidad Católica de Manizales1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Remote sensing applied to cocoa crop identification, a thematic review</dc:title><dc:creator>Cuellar-Escobar, Luisa Fernanda</dc:creator><dc:creator>Henao-Céspedes, Vladimir</dc:creator><dc:description>&lt;jats:p&gt;This article presents a thematic review of 25 publications related to the use of remote sensing techniques for the identification of cocoa crops from 2000 to 2023. Although the use of remote sensing techniques is widely used for mapping different covers because it is very useful in discriminating them, the generation of maps of cocoa crops presents challenges due to their spectral behavior similar to that of forests. This is because cocoa cultivation, being an agroforestry system that is developed in association with timber trees, causes the classification algorithms used to fail to differentiate between forest cover and cocoa crops. For this reason, this study seeks to investigate the different remote sensing techniques used in the mapping of cocoa crops, as well as an analysis of the structure of the publications highlighting the connections between countries and the factors that motivated the authors to research this crop.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2025-10-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v15i5.pp4848-4855</dc:identifier><dc:identifier>10.11591/ijece.v15i5.pp4848-4855</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 15 No 5 (2025); 4848</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/38349/18453</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>