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How can aerial imagery and vegetation indices algorithms monitor the geotagged crop?


Citation

Jeya Kumaran, Vikneswaran and Mohidem, Nur Adibah and Che'Ya, Nik Norasma and Fazlil Ilahi, Wan Fazilah and Arif Shah, Jasmin and Sahwee, Zulhilmy and Yusof, Norhakim and Omar, Mohammad Husni (2024) How can aerial imagery and vegetation indices algorithms monitor the geotagged crop? Egyptian Journal of Remote Sensing and Space Science, 27 (4). pp. 628-636. ISSN 1110-9823; eISSN: 2090-2476

Abstract

There is very little to no literature on the use of geotagging to monitor crops from aerial photos, even though many technologies have been created to do so. Current crop monitoring methods, relying on field data and lab analysis, are inefficient due to high labor, time, and potential harm, limiting their broad use. With the use of vegetation indices (VI) and geotagging, this paper highlights the benefits of crop-specific monitoring with unmanned aerial vehicles (UAV). This study systematically searched the original articles published from the 1st of January 2016 to the 7th of October 2021 in the databases of Scopus, ScienceDirect, Commonwealth Agricultural Bureaux (CAB) Direct, and Web of Science (WoS) using Boolean string: “aerial imagery” AND “vegetation index” OR “vegetation indices“ AND “crop”. Out of the papers identified, 28 eligible studies did meet our inclusion criteria and were evaluated. This review thoroughly discusses the advantages of aerial imagery, vegetation indices, and geotagging tools in the context of crop monitoring. It was found that geotagged crop monitoring using UAV empowers farmers with data-driven insights using vegetation indices, enabling them to make informed decisions before acting, transforming agriculture towards a digital future. This study offers valuable insights for researchers and industry players, helping them identify effective and context-specific crop monitoring strategies for diverse plantations, crops, and budgets. Moreover, by utilizing the advanced computational capabilities of artificial intelligence (AI), we can analyze a wide range of vegetation indices to gain a comprehensive understanding of crop health and conduct accurate predictions.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Agriculture
Faculty of Engineering
Institute of Tropical Agriculture and Food Security
DOI Number: https://doi.org/10.1016/j.ejrs.2024.08.003
Publisher: Elsevier B.V.
Keywords: Aerial imagery; Crop monitoring; Geotagging; Vegetation index
Depositing User: Ms. Zaimah Saiful Yazan
Date Deposited: 23 Sep 2025 02:07
Last Modified: 23 Sep 2025 02:07
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/j.ejrs.2024.08.003
URI: http://psasir.upm.edu.my/id/eprint/119790
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