Application of multispectral UAV for paddy growth monitoring in Jitra, Kedah, Malaysia

Rice is the staple food for most people in Southeast Asia, mainly Malaysia. Unfortunately, Malaysia does not reach a 100% self-sufficiency level on rice production due to inefficiency of rice farm management, pest and disease outbreak, poorly irrigation system, and climate change. Each spectral band...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IOP conference series. Earth and environmental science 2022-06, Vol.1038 (1), p.12053
Hauptverfasser: Mohidem, N A, Jaafar, S, Rosle, R, Che’Ya, N N, Arif Shah, J, Fazlil Ilahi, W F, Zainol, W N Z, Berahim, Z, Omar, M H, Ismail, M R
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 1
container_start_page 12053
container_title IOP conference series. Earth and environmental science
container_volume 1038
creator Mohidem, N A
Jaafar, S
Rosle, R
Che’Ya, N N
Arif Shah, J
Fazlil Ilahi, W F
Zainol, W N Z
Berahim, Z
Omar, M H
Ismail, M R
description Rice is the staple food for most people in Southeast Asia, mainly Malaysia. Unfortunately, Malaysia does not reach a 100% self-sufficiency level on rice production due to inefficiency of rice farm management, pest and disease outbreak, poorly irrigation system, and climate change. Each spectral band of electromagnetic signature in the rice crops can be identified to analyse the crop condition based on the reflectance value. Therefore, unmanned aerial vehicle (UAV) can capture different spectral band images of the rice field depending on the sensors used. This study aims to produce a paddy growth map based on the normalized difference vegetative index (NDVI) value and validate the paddy growth map using the soil plant analysis development (SPAD) data. This study was carried out at the paddy field planted with PadiU Putra rice variety in Muda Agricultural Development Authority (MADA), Jitra in Kedah. Three reading samples for each point at the paddy field within 1 m radius were recorded. Then, the samples from each point were scanned using SPAD chlorophyll meter. The image data were collected using multispectral and RGB cameras at the altitude of 60 m, and a calibrated reflectance panel was used to calibrate the image. Ground control point (GCP) was placed at the four corners of the study plot, and it was being used as a georeferencing point for aerial imagery mapping. Those images were undergone orthomosaic process to produce a single overlapped image. NDVI was used to measure the healthy level of rice crops. NDVI map had shown the distribution of NDVI value across the study plot, which includes the healthy and less healthy vegetative area. SPAD value has no significant relationship with the aerial imagery of NDVI value. The NDVI map allows the farmers to monitor the paddy growth status and effectively improve their rice farm management. In the future, advanced classification methods based on the reflectance of weed, water, and soil can be prioritized and separated into different classes, whereby the NDVI map can be plotted on the paddy crops.
doi_str_mv 10.1088/1755-1315/1038/1/012053
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2679297855</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2679297855</sourcerecordid><originalsourceid>FETCH-LOGICAL-c278t-d917efb55ddba20eea2200d15950b6b1b99887f5b522632d3e81d3c9ff92ff763</originalsourceid><addsrcrecordid>eNqFkF1LwzAUhoMoOKe_wYBXwuryYZrmcoz5OfFCt9uQNsmW0TUx7ZD9e1sqE0Hw6pzDed5z4AHgEqMbjLJsjDljCaaYjTGi7ThGmCBGj8DgsDk-9IifgrO63iCU8lsqBmA5CaF0hWqcr6C3cLsrG1cHUzRRlXAxWULrIwxK6z1cRf_ZrOHWV67x0VUr6Cr45FpyBJ-NVusRfFGl2tdOnYMTq8raXHzXIVjczd6nD8n89f5xOpknBeFZk2iBubE5Y1rniiBjFCEIacwEQ3ma41yILOOW5YyQlBJNTYY1LYS1gljLUzoEV_3dEP3HztSN3PhdrNqXkqRcEMEzxlqK91QRfV1HY2WIbqviXmIkO4my0yM7VbKTKLHsJbZJ2iedDz-n_09d_5Gazd5-czJoS78AHXyAhQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2679297855</pqid></control><display><type>article</type><title>Application of multispectral UAV for paddy growth monitoring in Jitra, Kedah, Malaysia</title><source>Institute of Physics Open Access Journal Titles</source><source>EZB-FREE-00999 freely available EZB journals</source><source>IOPscience extra</source><creator>Mohidem, N A ; Jaafar, S ; Rosle, R ; Che’Ya, N N ; Arif Shah, J ; Fazlil Ilahi, W F ; Zainol, W N Z ; Berahim, Z ; Omar, M H ; Ismail, M R</creator><creatorcontrib>Mohidem, N A ; Jaafar, S ; Rosle, R ; Che’Ya, N N ; Arif Shah, J ; Fazlil Ilahi, W F ; Zainol, W N Z ; Berahim, Z ; Omar, M H ; Ismail, M R</creatorcontrib><description>Rice is the staple food for most people in Southeast Asia, mainly Malaysia. Unfortunately, Malaysia does not reach a 100% self-sufficiency level on rice production due to inefficiency of rice farm management, pest and disease outbreak, poorly irrigation system, and climate change. Each spectral band of electromagnetic signature in the rice crops can be identified to analyse the crop condition based on the reflectance value. Therefore, unmanned aerial vehicle (UAV) can capture different spectral band images of the rice field depending on the sensors used. This study aims to produce a paddy growth map based on the normalized difference vegetative index (NDVI) value and validate the paddy growth map using the soil plant analysis development (SPAD) data. This study was carried out at the paddy field planted with PadiU Putra rice variety in Muda Agricultural Development Authority (MADA), Jitra in Kedah. Three reading samples for each point at the paddy field within 1 m radius were recorded. Then, the samples from each point were scanned using SPAD chlorophyll meter. The image data were collected using multispectral and RGB cameras at the altitude of 60 m, and a calibrated reflectance panel was used to calibrate the image. Ground control point (GCP) was placed at the four corners of the study plot, and it was being used as a georeferencing point for aerial imagery mapping. Those images were undergone orthomosaic process to produce a single overlapped image. NDVI was used to measure the healthy level of rice crops. NDVI map had shown the distribution of NDVI value across the study plot, which includes the healthy and less healthy vegetative area. SPAD value has no significant relationship with the aerial imagery of NDVI value. The NDVI map allows the farmers to monitor the paddy growth status and effectively improve their rice farm management. In the future, advanced classification methods based on the reflectance of weed, water, and soil can be prioritized and separated into different classes, whereby the NDVI map can be plotted on the paddy crops.</description><identifier>ISSN: 1755-1307</identifier><identifier>EISSN: 1755-1315</identifier><identifier>DOI: 10.1088/1755-1315/1038/1/012053</identifier><language>eng</language><publisher>Bristol: IOP Publishing</publisher><subject>Agricultural development ; Cameras ; Cereal crops ; Chlorophyll ; Climate change ; Crop production ; Crops ; Farm management ; Farms ; Imagery ; Irrigation systems ; Normalized difference vegetative index ; Reflectance ; Rice ; Rice fields ; Soil analysis ; Soil water ; Soils ; Unmanned aerial vehicles ; Vegetation index</subject><ispartof>IOP conference series. Earth and environmental science, 2022-06, Vol.1038 (1), p.12053</ispartof><rights>Published under licence by IOP Publishing Ltd</rights><rights>Published under licence by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c278t-d917efb55ddba20eea2200d15950b6b1b99887f5b522632d3e81d3c9ff92ff763</citedby><cites>FETCH-LOGICAL-c278t-d917efb55ddba20eea2200d15950b6b1b99887f5b522632d3e81d3c9ff92ff763</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1755-1315/1038/1/012053/pdf$$EPDF$$P50$$Giop$$Hfree_for_read</linktopdf><link.rule.ids>314,780,784,27924,27925,38868,38890,53840,53867</link.rule.ids></links><search><creatorcontrib>Mohidem, N A</creatorcontrib><creatorcontrib>Jaafar, S</creatorcontrib><creatorcontrib>Rosle, R</creatorcontrib><creatorcontrib>Che’Ya, N N</creatorcontrib><creatorcontrib>Arif Shah, J</creatorcontrib><creatorcontrib>Fazlil Ilahi, W F</creatorcontrib><creatorcontrib>Zainol, W N Z</creatorcontrib><creatorcontrib>Berahim, Z</creatorcontrib><creatorcontrib>Omar, M H</creatorcontrib><creatorcontrib>Ismail, M R</creatorcontrib><title>Application of multispectral UAV for paddy growth monitoring in Jitra, Kedah, Malaysia</title><title>IOP conference series. Earth and environmental science</title><addtitle>IOP Conf. Ser.: Earth Environ. Sci</addtitle><description>Rice is the staple food for most people in Southeast Asia, mainly Malaysia. Unfortunately, Malaysia does not reach a 100% self-sufficiency level on rice production due to inefficiency of rice farm management, pest and disease outbreak, poorly irrigation system, and climate change. Each spectral band of electromagnetic signature in the rice crops can be identified to analyse the crop condition based on the reflectance value. Therefore, unmanned aerial vehicle (UAV) can capture different spectral band images of the rice field depending on the sensors used. This study aims to produce a paddy growth map based on the normalized difference vegetative index (NDVI) value and validate the paddy growth map using the soil plant analysis development (SPAD) data. This study was carried out at the paddy field planted with PadiU Putra rice variety in Muda Agricultural Development Authority (MADA), Jitra in Kedah. Three reading samples for each point at the paddy field within 1 m radius were recorded. Then, the samples from each point were scanned using SPAD chlorophyll meter. The image data were collected using multispectral and RGB cameras at the altitude of 60 m, and a calibrated reflectance panel was used to calibrate the image. Ground control point (GCP) was placed at the four corners of the study plot, and it was being used as a georeferencing point for aerial imagery mapping. Those images were undergone orthomosaic process to produce a single overlapped image. NDVI was used to measure the healthy level of rice crops. NDVI map had shown the distribution of NDVI value across the study plot, which includes the healthy and less healthy vegetative area. SPAD value has no significant relationship with the aerial imagery of NDVI value. The NDVI map allows the farmers to monitor the paddy growth status and effectively improve their rice farm management. In the future, advanced classification methods based on the reflectance of weed, water, and soil can be prioritized and separated into different classes, whereby the NDVI map can be plotted on the paddy crops.</description><subject>Agricultural development</subject><subject>Cameras</subject><subject>Cereal crops</subject><subject>Chlorophyll</subject><subject>Climate change</subject><subject>Crop production</subject><subject>Crops</subject><subject>Farm management</subject><subject>Farms</subject><subject>Imagery</subject><subject>Irrigation systems</subject><subject>Normalized difference vegetative index</subject><subject>Reflectance</subject><subject>Rice</subject><subject>Rice fields</subject><subject>Soil analysis</subject><subject>Soil water</subject><subject>Soils</subject><subject>Unmanned aerial vehicles</subject><subject>Vegetation index</subject><issn>1755-1307</issn><issn>1755-1315</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>O3W</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkF1LwzAUhoMoOKe_wYBXwuryYZrmcoz5OfFCt9uQNsmW0TUx7ZD9e1sqE0Hw6pzDed5z4AHgEqMbjLJsjDljCaaYjTGi7ThGmCBGj8DgsDk-9IifgrO63iCU8lsqBmA5CaF0hWqcr6C3cLsrG1cHUzRRlXAxWULrIwxK6z1cRf_ZrOHWV67x0VUr6Cr45FpyBJ-NVusRfFGl2tdOnYMTq8raXHzXIVjczd6nD8n89f5xOpknBeFZk2iBubE5Y1rniiBjFCEIacwEQ3ma41yILOOW5YyQlBJNTYY1LYS1gljLUzoEV_3dEP3HztSN3PhdrNqXkqRcEMEzxlqK91QRfV1HY2WIbqviXmIkO4my0yM7VbKTKLHsJbZJ2iedDz-n_09d_5Gazd5-czJoS78AHXyAhQ</recordid><startdate>20220601</startdate><enddate>20220601</enddate><creator>Mohidem, N A</creator><creator>Jaafar, S</creator><creator>Rosle, R</creator><creator>Che’Ya, N N</creator><creator>Arif Shah, J</creator><creator>Fazlil Ilahi, W F</creator><creator>Zainol, W N Z</creator><creator>Berahim, Z</creator><creator>Omar, M H</creator><creator>Ismail, M R</creator><general>IOP Publishing</general><scope>O3W</scope><scope>TSCCA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope></search><sort><creationdate>20220601</creationdate><title>Application of multispectral UAV for paddy growth monitoring in Jitra, Kedah, Malaysia</title><author>Mohidem, N A ; Jaafar, S ; Rosle, R ; Che’Ya, N N ; Arif Shah, J ; Fazlil Ilahi, W F ; Zainol, W N Z ; Berahim, Z ; Omar, M H ; Ismail, M R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c278t-d917efb55ddba20eea2200d15950b6b1b99887f5b522632d3e81d3c9ff92ff763</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Agricultural development</topic><topic>Cameras</topic><topic>Cereal crops</topic><topic>Chlorophyll</topic><topic>Climate change</topic><topic>Crop production</topic><topic>Crops</topic><topic>Farm management</topic><topic>Farms</topic><topic>Imagery</topic><topic>Irrigation systems</topic><topic>Normalized difference vegetative index</topic><topic>Reflectance</topic><topic>Rice</topic><topic>Rice fields</topic><topic>Soil analysis</topic><topic>Soil water</topic><topic>Soils</topic><topic>Unmanned aerial vehicles</topic><topic>Vegetation index</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mohidem, N A</creatorcontrib><creatorcontrib>Jaafar, S</creatorcontrib><creatorcontrib>Rosle, R</creatorcontrib><creatorcontrib>Che’Ya, N N</creatorcontrib><creatorcontrib>Arif Shah, J</creatorcontrib><creatorcontrib>Fazlil Ilahi, W F</creatorcontrib><creatorcontrib>Zainol, W N Z</creatorcontrib><creatorcontrib>Berahim, Z</creatorcontrib><creatorcontrib>Omar, M H</creatorcontrib><creatorcontrib>Ismail, M R</creatorcontrib><collection>Institute of Physics Open Access Journal Titles</collection><collection>IOPscience (Open Access)</collection><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Environmental Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><jtitle>IOP conference series. Earth and environmental science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mohidem, N A</au><au>Jaafar, S</au><au>Rosle, R</au><au>Che’Ya, N N</au><au>Arif Shah, J</au><au>Fazlil Ilahi, W F</au><au>Zainol, W N Z</au><au>Berahim, Z</au><au>Omar, M H</au><au>Ismail, M R</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of multispectral UAV for paddy growth monitoring in Jitra, Kedah, Malaysia</atitle><jtitle>IOP conference series. Earth and environmental science</jtitle><addtitle>IOP Conf. Ser.: Earth Environ. Sci</addtitle><date>2022-06-01</date><risdate>2022</risdate><volume>1038</volume><issue>1</issue><spage>12053</spage><pages>12053-</pages><issn>1755-1307</issn><eissn>1755-1315</eissn><abstract>Rice is the staple food for most people in Southeast Asia, mainly Malaysia. Unfortunately, Malaysia does not reach a 100% self-sufficiency level on rice production due to inefficiency of rice farm management, pest and disease outbreak, poorly irrigation system, and climate change. Each spectral band of electromagnetic signature in the rice crops can be identified to analyse the crop condition based on the reflectance value. Therefore, unmanned aerial vehicle (UAV) can capture different spectral band images of the rice field depending on the sensors used. This study aims to produce a paddy growth map based on the normalized difference vegetative index (NDVI) value and validate the paddy growth map using the soil plant analysis development (SPAD) data. This study was carried out at the paddy field planted with PadiU Putra rice variety in Muda Agricultural Development Authority (MADA), Jitra in Kedah. Three reading samples for each point at the paddy field within 1 m radius were recorded. Then, the samples from each point were scanned using SPAD chlorophyll meter. The image data were collected using multispectral and RGB cameras at the altitude of 60 m, and a calibrated reflectance panel was used to calibrate the image. Ground control point (GCP) was placed at the four corners of the study plot, and it was being used as a georeferencing point for aerial imagery mapping. Those images were undergone orthomosaic process to produce a single overlapped image. NDVI was used to measure the healthy level of rice crops. NDVI map had shown the distribution of NDVI value across the study plot, which includes the healthy and less healthy vegetative area. SPAD value has no significant relationship with the aerial imagery of NDVI value. The NDVI map allows the farmers to monitor the paddy growth status and effectively improve their rice farm management. In the future, advanced classification methods based on the reflectance of weed, water, and soil can be prioritized and separated into different classes, whereby the NDVI map can be plotted on the paddy crops.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1755-1315/1038/1/012053</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1755-1307
ispartof IOP conference series. Earth and environmental science, 2022-06, Vol.1038 (1), p.12053
issn 1755-1307
1755-1315
language eng
recordid cdi_proquest_journals_2679297855
source Institute of Physics Open Access Journal Titles; EZB-FREE-00999 freely available EZB journals; IOPscience extra
subjects Agricultural development
Cameras
Cereal crops
Chlorophyll
Climate change
Crop production
Crops
Farm management
Farms
Imagery
Irrigation systems
Normalized difference vegetative index
Reflectance
Rice
Rice fields
Soil analysis
Soil water
Soils
Unmanned aerial vehicles
Vegetation index
title Application of multispectral UAV for paddy growth monitoring in Jitra, Kedah, Malaysia
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T06%3A30%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Application%20of%20multispectral%20UAV%20for%20paddy%20growth%20monitoring%20in%20Jitra,%20Kedah,%20Malaysia&rft.jtitle=IOP%20conference%20series.%20Earth%20and%20environmental%20science&rft.au=Mohidem,%20N%20A&rft.date=2022-06-01&rft.volume=1038&rft.issue=1&rft.spage=12053&rft.pages=12053-&rft.issn=1755-1307&rft.eissn=1755-1315&rft_id=info:doi/10.1088/1755-1315/1038/1/012053&rft_dat=%3Cproquest_cross%3E2679297855%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2679297855&rft_id=info:pmid/&rfr_iscdi=true