Weed Detection in Rice Fields Using Remote Sensing Technique: A Review
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 fi...
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2021
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oai:doaj.org-article:90751a5326614ac1ab3efef3d0a0fc4c2021-11-25T16:35:42ZWeed Detection in Rice Fields Using Remote Sensing Technique: A Review10.3390/app1122107012076-3417https://doaj.org/article/90751a5326614ac1ab3efef3d0a0fc4c2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10701https://doaj.org/toc/2076-3417This 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.Rhushalshafira RosleNik Norasma Che’YaYuhao AngFariq RahmatAimrun WayayokZulkarami BerahimWan Fazilah Fazlil IlahiMohd Razi IsmailMohamad Husni OmarMDPI AGarticleinvasive plantsprecision agricultureremote sensingrice farmingsite-specific weed managementTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10701, p 10701 (2021) |
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invasive plants precision agriculture remote sensing rice farming site-specific weed management Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 |
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invasive plants precision agriculture remote sensing rice farming site-specific weed management Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Rhushalshafira Rosle Nik Norasma Che’Ya Yuhao Ang Fariq Rahmat Aimrun Wayayok Zulkarami Berahim Wan Fazilah Fazlil Ilahi Mohd Razi Ismail Mohamad Husni Omar Weed Detection in Rice Fields Using Remote Sensing Technique: A Review |
description |
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. |
format |
article |
author |
Rhushalshafira Rosle Nik Norasma Che’Ya Yuhao Ang Fariq Rahmat Aimrun Wayayok Zulkarami Berahim Wan Fazilah Fazlil Ilahi Mohd Razi Ismail Mohamad Husni Omar |
author_facet |
Rhushalshafira Rosle Nik Norasma Che’Ya Yuhao Ang Fariq Rahmat Aimrun Wayayok Zulkarami Berahim Wan Fazilah Fazlil Ilahi Mohd Razi Ismail Mohamad Husni Omar |
author_sort |
Rhushalshafira Rosle |
title |
Weed Detection in Rice Fields Using Remote Sensing Technique: A Review |
title_short |
Weed Detection in Rice Fields Using Remote Sensing Technique: A Review |
title_full |
Weed Detection in Rice Fields Using Remote Sensing Technique: A Review |
title_fullStr |
Weed Detection in Rice Fields Using Remote Sensing Technique: A Review |
title_full_unstemmed |
Weed Detection in Rice Fields Using Remote Sensing Technique: A Review |
title_sort |
weed detection in rice fields using remote sensing technique: a review |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/90751a5326614ac1ab3efef3d0a0fc4c |
work_keys_str_mv |
AT rhushalshafirarosle weeddetectioninricefieldsusingremotesensingtechniqueareview AT niknorasmacheya weeddetectioninricefieldsusingremotesensingtechniqueareview AT yuhaoang weeddetectioninricefieldsusingremotesensingtechniqueareview AT fariqrahmat weeddetectioninricefieldsusingremotesensingtechniqueareview AT aimrunwayayok weeddetectioninricefieldsusingremotesensingtechniqueareview AT zulkaramiberahim weeddetectioninricefieldsusingremotesensingtechniqueareview AT wanfazilahfazlililahi weeddetectioninricefieldsusingremotesensingtechniqueareview AT mohdraziismail weeddetectioninricefieldsusingremotesensingtechniqueareview AT mohamadhusniomar weeddetectioninricefieldsusingremotesensingtechniqueareview |
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