Evaluation of UAV-Based RGB and Multispectral Vegetation Indices for Precision Agriculture in Palm Tree Cultivation

Precision farming relies on accurate vegetation monitoring to enhance crop productivity and promote sustainable agricultural practices. This study presents a comprehensive evaluation of Unmanned Aerial Vehicle (UAV)-based imaging for vegetation health assessment in a palm tree cultivation region in...

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Main Authors: S. M. Anzar, K. Sherin, A. Panthakkan, S. Al Mansoori, H. Al-Ahmad
Format: Article
Language:English
Published: Copernicus Publications 2025-07-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://isprs-archives.copernicus.org/articles/XLVIII-G-2025/163/2025/isprs-archives-XLVIII-G-2025-163-2025.pdf
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author S. M. Anzar
K. Sherin
A. Panthakkan
S. Al Mansoori
H. Al-Ahmad
author_facet S. M. Anzar
K. Sherin
A. Panthakkan
S. Al Mansoori
H. Al-Ahmad
author_sort S. M. Anzar
collection DOAJ
description Precision farming relies on accurate vegetation monitoring to enhance crop productivity and promote sustainable agricultural practices. This study presents a comprehensive evaluation of Unmanned Aerial Vehicle (UAV)-based imaging for vegetation health assessment in a palm tree cultivation region in Dubai. By comparing multispectral and Red, Green, and Blue (RGB) image data, we demonstrate that RGB-based vegetation indices offer performance comparable to more expensive multispectral indices, providing a cost-effective alternative for large-scale agricultural monitoring. Using UAVs equipped with multispectral sensors, indices such as Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) were computed to categorize vegetation into healthy, moderate, and stressed conditions. Simultaneously, RGB-based indices like Visible Atmospherically Resistant Index (VARI) and Modified Green Red Vegetation Index (MGRVI) delivered similar results in vegetation classification and stress detection. Our findings highlight the practical benefits of integrating RGB imagery into precision farming, reducing operational costs while maintaining accuracy in plant health monitoring. This research underscores the potential of UAV-based RGB imaging as a powerful tool for precision agriculture, enabling broader adoption of data-driven decision-making in crop management. By leveraging the strengths of both multispectral and RGB imaging, this work advances the state of UAV applications in agriculture, paving the way for more efficient and scalable farming solutions.
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spelling doaj-art-dda71179695f4ad89157fbabaeba1e242025-08-20T02:45:31ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342025-07-01XLVIII-G-202516317010.5194/isprs-archives-XLVIII-G-2025-163-2025Evaluation of UAV-Based RGB and Multispectral Vegetation Indices for Precision Agriculture in Palm Tree CultivationS. M. Anzar0K. Sherin1A. Panthakkan2S. Al Mansoori3H. Al-Ahmad4Department of Electronics and Communication, TKM College of Engineering, Kollam, IndiaDepartment of Electronics and Communication, MES College of Engineering, Kuttippuram, IndiaCollege of Engineering and IT, University of Dubai,Dubai, U.A.ERemote Sensing Department, Mohammed Bin Rashid Space Centre (MBRSC), Dubai, U.A.E.College of Engineering and IT, University of Dubai,Dubai, U.A.EPrecision farming relies on accurate vegetation monitoring to enhance crop productivity and promote sustainable agricultural practices. This study presents a comprehensive evaluation of Unmanned Aerial Vehicle (UAV)-based imaging for vegetation health assessment in a palm tree cultivation region in Dubai. By comparing multispectral and Red, Green, and Blue (RGB) image data, we demonstrate that RGB-based vegetation indices offer performance comparable to more expensive multispectral indices, providing a cost-effective alternative for large-scale agricultural monitoring. Using UAVs equipped with multispectral sensors, indices such as Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) were computed to categorize vegetation into healthy, moderate, and stressed conditions. Simultaneously, RGB-based indices like Visible Atmospherically Resistant Index (VARI) and Modified Green Red Vegetation Index (MGRVI) delivered similar results in vegetation classification and stress detection. Our findings highlight the practical benefits of integrating RGB imagery into precision farming, reducing operational costs while maintaining accuracy in plant health monitoring. This research underscores the potential of UAV-based RGB imaging as a powerful tool for precision agriculture, enabling broader adoption of data-driven decision-making in crop management. By leveraging the strengths of both multispectral and RGB imaging, this work advances the state of UAV applications in agriculture, paving the way for more efficient and scalable farming solutions.https://isprs-archives.copernicus.org/articles/XLVIII-G-2025/163/2025/isprs-archives-XLVIII-G-2025-163-2025.pdf
spellingShingle S. M. Anzar
K. Sherin
A. Panthakkan
S. Al Mansoori
H. Al-Ahmad
Evaluation of UAV-Based RGB and Multispectral Vegetation Indices for Precision Agriculture in Palm Tree Cultivation
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title Evaluation of UAV-Based RGB and Multispectral Vegetation Indices for Precision Agriculture in Palm Tree Cultivation
title_full Evaluation of UAV-Based RGB and Multispectral Vegetation Indices for Precision Agriculture in Palm Tree Cultivation
title_fullStr Evaluation of UAV-Based RGB and Multispectral Vegetation Indices for Precision Agriculture in Palm Tree Cultivation
title_full_unstemmed Evaluation of UAV-Based RGB and Multispectral Vegetation Indices for Precision Agriculture in Palm Tree Cultivation
title_short Evaluation of UAV-Based RGB and Multispectral Vegetation Indices for Precision Agriculture in Palm Tree Cultivation
title_sort evaluation of uav based rgb and multispectral vegetation indices for precision agriculture in palm tree cultivation
url https://isprs-archives.copernicus.org/articles/XLVIII-G-2025/163/2025/isprs-archives-XLVIII-G-2025-163-2025.pdf
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