# Weed Detection in Rice Fields Using Remote Sensing Technique: A Review
###### 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.  
invasive plants; precision agriculture; remote sensing; rice farming; site-specific weed management +
Footnote †: journal:tance and reduced the choices of herbicides to use [4; 5]. Figure 1 illustrates the herbicides usage in controlling weeds for each continent in percentage.  
It is necessary to construct systematic and strategic planning to improve the precision agriculture (PA) sector, especially in weed management, to control and increase yield production, leading to a better economy for the country and farmers. Therefore, remote sensing-based techniques were used to construct and optimize weed management. Remote sensing is a comprehensive framework that monitors and captures earth surface images without direct contact with it. In PA sectors, the data gathered can be used in various applications, such as monitoring rice's morphology [6], yield estimation [7], and mapping irrigated areas for food security and water resource management [8]. However, even though remote sensing has been widely used in weed management, it may not be a permanently adopted by developing countries anytime soon since local farmers still prefer the traditional practices.  
Thus, this paper aims to review and discuss the techniques and algorithms used in remote sensing to construct systematic and strategic planning to improve precision agriculture in weed management. As a result, researchers can adapt the knowledge of controlling weed presence and increasing yield production, especially in developing countries. This study's focus was limited to weed detection using a remote sensing platform in the paddy field. However, weed detection in other crops using remote sensing was also included.  
This paper is organized into eight sections. Section 1 briefly explains this study's goal in implementing remote sensing techniques into the precision agriculture (PA) sector. Section 2 explains the strategy used to search through the scientific database for relevant publications. Meanwhile, Section 3 discusses the importance of rice and what has been carried out to increase yield. Section 4 highlights the best stage to control weed in paddy, weed types, and traditional farming practices. Section 5 presents the literature covering various types of weed detection using remote sensing techniques. Section 6 reviews the impact of inadequate and good weed management on crops, yield, and economy. Section 7 deliberates the future direction of remote sensing techniques in weed detection. Lastly, in Section 8, the conclusions are presented.