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Integration of Unmanned Aerial Vehicle and Multispectral Sensor for Paddy Growth Monitoring Application: A Review

Nur Adibah Mohidem, Suhami Jaafar and Nik Norasma Che’Ya

Pertanika Journal of Science & Technology, Volume 32, Issue 2, March 2024

DOI: https://doi.org/10.47836/pjst.32.2.04

Keywords: Multispectral, normalised difference vegetation index, paddy field, soil plant analysis development, unmanned aerial vehicle

Published on: 26 March 2024

Using a conventional approach via visual observation on the ground, farmers encounter difficulties monitoring the entire paddy field area, and it is time-consuming to do manually. The application of unmanned aerial vehicles (UAVs) could help farmers optimise inputs such as water and fertiliser to increase yield, productivity, and quality, allowing them to manage their operations at lower costs and with minimum environmental impact. Therefore, this article aims to provide an overview of the integration of UAV and multispectral sensors in monitoring paddy growth applications based on vegetation indices and soil plant analysis development (SPAD) data. The article briefly describes current rice production in Malaysia and a general concept of precision agriculture technologies. The application of multispectral sensors integrated with UAVs in monitoring paddy growth is highlighted. Previous research on aerial imagery derived from the multispectral sensor using the normalised difference vegetation index (NDVI) is explored to provide information regarding the health condition of the paddy. Validation of the paddy growth map using SPAD data in determining the leaf’s relative chlorophyll and nitrogen content is also being discussed. Implementation of precision agriculture among low-income farmers could provide valuable insights into the practical implications of this review. With ongoing education, training and experience, farmers can eventually manage the UAV independently in the field. This article concludes with a future research direction regarding the production of growth maps for other crops using a variety of vegetation indices and map validation using the SPAD metre values.

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JST-4254-2023

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