Weed Detection in Rice Fields Using Remote Sensing Technique: A Review

Nik Norasma Che’Ya,Yuhao Ang,Wan Fazilah Fazlil Ilahi,Aimrun Wayayok,Rhushalshafira Rosle,Mohamad Husni Omar,Mohd Razi Ismail,Fariq Rahmat,Zulkarami Berahim

doi:10.3390/app112210701

Abstract

This paper reviewed the weed problems in agriculture and how remote sensing techniques can detect weeds in rice fields. The comparison of weed detection between traditional practices and automated detection using remote sensing platforms is discussed. The ideal stage for controlling weeds in rice fields was highlighted, and the types of weeds usually found in paddy fields were listed. This paper will discuss weed detection using remote sensing techniques, and algorithms commonly used to differentiate them from crops are deliberated. However, weed detection in rice fields using remote sensing platforms is still in its early stages; weed detection in other crops is also discussed. Results show that machine learning (ML) and deep learning (DL) remote sensing techniques have successfully produced a high accuracy map for detecting weeds in crops using RS platforms. Therefore, this technology positively impacts weed management in many aspects, especially in terms of the economic perspective. The implementation of this technology into agricultural development could be extended further.

Highlights

It is undoubtful that weeds, known as invasive plants, have their roles in the ecosystem
Even though various platforms are available for data gathering, unmanned aerial vehicles (UAV) are the best for detecting weeds in paddy due to their availability, high-quality data delivery, and ease of handling
To decide which algorithm best suits our research, we need to know what types of weeds we are dealing with by observing their types in paddy fields

Summary

Introduction

It is undoubtful that weeds, known as invasive plants, have their roles in the ecosystem. Their presence in crops such as rice, oil palm, rubber, and other mass plantations influences productivity, causes significant economic consequences, decreases land prices, and reduces company profits [1]. A statistic released by the Food and Agriculture Organization of the United Nations (FAO) for the years 1990 to 2019 showed that the Asia continent had used approximately 805,412 tonnes of herbicides in controlling the presence of weeds in various types of crops, followed by the Americas (593,619 tonnes), Europe (179,799 tonnes), Oceania (29,309 tonnes), and Africa (21,117 tonnes) [3]. Too much dependence on herbicides usage to control weeds to maximize yield production has caused herbicide resistance and reduced the choices of herbicides to use [4,5].

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