Evaluating the health and disease level of oil palm trees using vegetation indices / Atika Baizura Zahirulail

The oil palm vegetation in Malaysia plays a significant role in the country due to the economic growth, and it must be well managed to help the plant produce healthy yields. When the oil palm trees grow widely, it will be challenging to monitor manually due to energy, cost, and time constraints then...

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Main Author:	Zahirulail, Atika Baizura
Format:	Thesis
Language:	English
Published:	2022
Subjects:	Aerial geography Remote Sensing
Online Access:	https://ir.uitm.edu.my/id/eprint/57083/1/57083.pdf
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id	my-uitm-ir.57083
record_format	uketd_dc
spelling	my-uitm-ir.570832022-06-14T07:01:21Z Evaluating the health and disease level of oil palm trees using vegetation indices / Atika Baizura Zahirulail 2022-03-15 Zahirulail, Atika Baizura Aerial geography Remote Sensing The oil palm vegetation in Malaysia plays a significant role in the country due to the economic growth, and it must be well managed to help the plant produce healthy yields. When the oil palm trees grow widely, it will be challenging to monitor manually due to energy, cost, and time constraints then will cause the plants to be diseased and not grow well. Therefore, this study aims to (i. classify the vegetation health of oil palm trees using the vegetation indices, (ii. identify the chlorophyll content using canopy chlorophyll content index (CCCI), and (iii. determine the relationship between the vegetation health and chlorophyll content of oil palm trees plantation. The method in this study is to classify the disease symptom of oil palm trees from Sentinel-2B using the vegetation indices. Then compute the chlorophyll content with different vegetation indices that indicate the condition of the oil palm plantation. Therefore, the regression analysis is used to perform the relationship between oil palm disease symptoms and chlorophyll content then execute the result of oil palm trees condition either healthy or vice versa. This study is performed fully in Python language. Otherwise, this study expects that the oil palm tree's health and disease level can be detected using the Remote Sensing technique and helps the industry produce quality and good results from the oil palm tree and impact the country's economy. 2022-03 Thesis https://ir.uitm.edu.my/id/eprint/57083/ https://ir.uitm.edu.my/id/eprint/57083/1/57083.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of Architecture, Planning and Surveying
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Aerial geography Remote Sensing
spellingShingle	Aerial geography Remote Sensing Zahirulail, Atika Baizura Evaluating the health and disease level of oil palm trees using vegetation indices / Atika Baizura Zahirulail
description	The oil palm vegetation in Malaysia plays a significant role in the country due to the economic growth, and it must be well managed to help the plant produce healthy yields. When the oil palm trees grow widely, it will be challenging to monitor manually due to energy, cost, and time constraints then will cause the plants to be diseased and not grow well. Therefore, this study aims to (i. classify the vegetation health of oil palm trees using the vegetation indices, (ii. identify the chlorophyll content using canopy chlorophyll content index (CCCI), and (iii. determine the relationship between the vegetation health and chlorophyll content of oil palm trees plantation. The method in this study is to classify the disease symptom of oil palm trees from Sentinel-2B using the vegetation indices. Then compute the chlorophyll content with different vegetation indices that indicate the condition of the oil palm plantation. Therefore, the regression analysis is used to perform the relationship between oil palm disease symptoms and chlorophyll content then execute the result of oil palm trees condition either healthy or vice versa. This study is performed fully in Python language. Otherwise, this study expects that the oil palm tree's health and disease level can be detected using the Remote Sensing technique and helps the industry produce quality and good results from the oil palm tree and impact the country's economy.
format	Thesis
qualification_level	Bachelor degree
author	Zahirulail, Atika Baizura
author_facet	Zahirulail, Atika Baizura
author_sort	Zahirulail, Atika Baizura
title	Evaluating the health and disease level of oil palm trees using vegetation indices / Atika Baizura Zahirulail
title_short	Evaluating the health and disease level of oil palm trees using vegetation indices / Atika Baizura Zahirulail
title_full	Evaluating the health and disease level of oil palm trees using vegetation indices / Atika Baizura Zahirulail
title_fullStr	Evaluating the health and disease level of oil palm trees using vegetation indices / Atika Baizura Zahirulail
title_full_unstemmed	Evaluating the health and disease level of oil palm trees using vegetation indices / Atika Baizura Zahirulail
title_sort	evaluating the health and disease level of oil palm trees using vegetation indices / atika baizura zahirulail
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Architecture, Planning and Surveying
publishDate	2022
url	https://ir.uitm.edu.my/id/eprint/57083/1/57083.pdf
_version_	1783734966769680384

Evaluating the health and disease level of oil palm trees using vegetation indices / Atika Baizura Zahirulail

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