Rubber disease mapping using low altitude multispectral images

One of the most important rubber leaf diseases in Malaysia is Oidium leaf disease. A Severe outbreak of this disease may cause an annual yield loss with 20% decrement of latex production in a rubber plantation. Currently, data acquisition is obtained manually which results in lack effectiveness, cos...

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Main Author:	Abdul Hamid, Nurmi Rohayu
Format:	Thesis
Language:	English
Published:	2017
Subjects:	G70.39-70.6 Remote sensing
Online Access:	http://eprints.utm.my/id/eprint/78872/1/NurmiRohayuAbdulMFGHT2017.pdf
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id	my-utm-ep.78872
record_format	uketd_dc
spelling	my-utm-ep.788722018-09-17T07:15:48Z Rubber disease mapping using low altitude multispectral images 2017-06 Abdul Hamid, Nurmi Rohayu G70.39-70.6 Remote sensing One of the most important rubber leaf diseases in Malaysia is Oidium leaf disease. A Severe outbreak of this disease may cause an annual yield loss with 20% decrement of latex production in a rubber plantation. Currently, data acquisition is obtained manually which results in lack effectiveness, costly, and typically labour incentive. However, recent technology using unmanned aerial vehicle (UAV) has potential to overcome these issues. The UAV is able to facilitate spatially and allow temporal flexible data acquisition using a compact camera payload. Therefore, this study intention is to identify the health of rubber tree that affected by Oidium leaf disease using low altitude remote sensing images that acquired from UAV platform. The study area is carried out at Experimental Rubber Plot, Research Station Malaysian Rubber Board, Kota Tinggi, Johor in order to generate the healthy, unhealthy and severe map. Those maps were produced using multiple regression analysis between spectral reflectance at blue (450 – 510 nm), green (530 – 590 nm), red (640 – 670 nm) and near-infrared (850 – 880 nm) based on UAV. Oidium leaf disease can be identified by low absorption of light at the red band and little at the near infrared band resulted of high reflectance at both bands. As a result, this study successfully to determine the condition of rubber tree caused by leaf disease using low-cost remote sensing technology which deploys the UAV and payload by the digital compact camera. 2017-06 Thesis http://eprints.utm.my/id/eprint/78872/ http://eprints.utm.my/id/eprint/78872/1/NurmiRohayuAbdulMFGHT2017.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:106619 masters Universiti Teknologi Malaysia, Faculty of Geoinformation and Real Estate Faculty of Geoinformation and Real Estate
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	G70.39-70.6 Remote sensing
spellingShingle	G70.39-70.6 Remote sensing Abdul Hamid, Nurmi Rohayu Rubber disease mapping using low altitude multispectral images
description	One of the most important rubber leaf diseases in Malaysia is Oidium leaf disease. A Severe outbreak of this disease may cause an annual yield loss with 20% decrement of latex production in a rubber plantation. Currently, data acquisition is obtained manually which results in lack effectiveness, costly, and typically labour incentive. However, recent technology using unmanned aerial vehicle (UAV) has potential to overcome these issues. The UAV is able to facilitate spatially and allow temporal flexible data acquisition using a compact camera payload. Therefore, this study intention is to identify the health of rubber tree that affected by Oidium leaf disease using low altitude remote sensing images that acquired from UAV platform. The study area is carried out at Experimental Rubber Plot, Research Station Malaysian Rubber Board, Kota Tinggi, Johor in order to generate the healthy, unhealthy and severe map. Those maps were produced using multiple regression analysis between spectral reflectance at blue (450 – 510 nm), green (530 – 590 nm), red (640 – 670 nm) and near-infrared (850 – 880 nm) based on UAV. Oidium leaf disease can be identified by low absorption of light at the red band and little at the near infrared band resulted of high reflectance at both bands. As a result, this study successfully to determine the condition of rubber tree caused by leaf disease using low-cost remote sensing technology which deploys the UAV and payload by the digital compact camera.
format	Thesis
qualification_level	Master's degree
author	Abdul Hamid, Nurmi Rohayu
author_facet	Abdul Hamid, Nurmi Rohayu
author_sort	Abdul Hamid, Nurmi Rohayu
title	Rubber disease mapping using low altitude multispectral images
title_short	Rubber disease mapping using low altitude multispectral images
title_full	Rubber disease mapping using low altitude multispectral images
title_fullStr	Rubber disease mapping using low altitude multispectral images
title_full_unstemmed	Rubber disease mapping using low altitude multispectral images
title_sort	rubber disease mapping using low altitude multispectral images
granting_institution	Universiti Teknologi Malaysia, Faculty of Geoinformation and Real Estate
granting_department	Faculty of Geoinformation and Real Estate
publishDate	2017
url	http://eprints.utm.my/id/eprint/78872/1/NurmiRohayuAbdulMFGHT2017.pdf
_version_	1747818092108447744

Rubber disease mapping using low altitude multispectral images

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