Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee

Oidium Leaf Disease is one of the most infected rubber leaf disease in Malaysia. A severe outbreak of this disease may cause an annual yield loss with 20% decrement of latex production in a rubber plantation. Recent technology using unmanned aerial vehicle (UAV) has potential to provide cost effecti...

Full description

Saved in:

Bibliographic Details
Main Author:	Roslee, Nurul Irafatin
Format:	Thesis
Language:	English
Published:	2020
Subjects:	Geographic information systems
Online Access:	https://ir.uitm.edu.my/id/eprint/28861/1/TD_NURUL%20IRAFATIN%20ROSLEE%20AP%20R%2019_5.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uitm-ir.28861
record_format	uketd_dc
spelling	my-uitm-ir.288612020-03-26T04:43:53Z Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee 2020-03-16 Roslee, Nurul Irafatin Geographic information systems Geometry. Trigonometry. Topology Oidium Leaf Disease is one of the most infected rubber leaf disease in Malaysia. A severe outbreak of this disease may cause an annual yield loss with 20% decrement of latex production in a rubber plantation. Recent technology using unmanned aerial vehicle (UAV) has potential to provide cost effective data acquisition for the estimation of rubber leaf disease such as Oidium Disease. The UAV is able to facilitate spatially and allow temporal flexible data acquisition using a compact camera payload. Thus, the aim of this study is to assess drone-based multispectral images for Oidium disease on rubber leaves using spectroradiometer. This study is carried out at Experimental Rubber Plot, Research Station Malaysian Rubber Board, Kota Tinggi, Johor. The map of Oidium Disease severity index level is generated by using Support Vector Machine (SVM) Classification. From the severity index level in the map, Oidium Disease was identified by low absorption of light at the red band (0.02) and medium absorption at near-infrared band (0.32). The level of absorption from the results indicates that the leaves have less chlorophyll since it was very severely infected with Oidium Disease. The finding of this study shows that low-cost remote sensing technology which deploys the UAV and digital compact camera is potentially can be used to determine the condition of rubber tree caused by leaves disease. 2020-03 Thesis https://ir.uitm.edu.my/id/eprint/28861/ https://ir.uitm.edu.my/id/eprint/28861/1/TD_NURUL%20IRAFATIN%20ROSLEE%20AP%20R%2019_5.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of Architecture, Planning and Surverying (R)
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Geographic information systems Geographic information systems
spellingShingle	Geographic information systems Geographic information systems Roslee, Nurul Irafatin Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee
description	Oidium Leaf Disease is one of the most infected rubber leaf disease in Malaysia. A severe outbreak of this disease may cause an annual yield loss with 20% decrement of latex production in a rubber plantation. Recent technology using unmanned aerial vehicle (UAV) has potential to provide cost effective data acquisition for the estimation of rubber leaf disease such as Oidium Disease. The UAV is able to facilitate spatially and allow temporal flexible data acquisition using a compact camera payload. Thus, the aim of this study is to assess drone-based multispectral images for Oidium disease on rubber leaves using spectroradiometer. This study is carried out at Experimental Rubber Plot, Research Station Malaysian Rubber Board, Kota Tinggi, Johor. The map of Oidium Disease severity index level is generated by using Support Vector Machine (SVM) Classification. From the severity index level in the map, Oidium Disease was identified by low absorption of light at the red band (0.02) and medium absorption at near-infrared band (0.32). The level of absorption from the results indicates that the leaves have less chlorophyll since it was very severely infected with Oidium Disease. The finding of this study shows that low-cost remote sensing technology which deploys the UAV and digital compact camera is potentially can be used to determine the condition of rubber tree caused by leaves disease.
format	Thesis
qualification_level	Bachelor degree
author	Roslee, Nurul Irafatin
author_facet	Roslee, Nurul Irafatin
author_sort	Roslee, Nurul Irafatin
title	Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee
title_short	Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee
title_full	Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee
title_fullStr	Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee
title_full_unstemmed	Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee
title_sort	assesment of oidium disease on rubber leaves by drone-based multispectral image / nurul irafatin roslee
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Architecture, Planning and Surverying (R)
publishDate	2020
url	https://ir.uitm.edu.my/id/eprint/28861/1/TD_NURUL%20IRAFATIN%20ROSLEE%20AP%20R%2019_5.pdf
_version_	1783734075038629888

Assesment of oidium disease on rubber leaves by drone-based multispectral image / Nurul Irafatin Roslee

Similar Items