Detection of rubber tree using image classification and vegetation indices / Nurhidayah Abidin

The rubber tree (Hevea brasiliensis is a tree of the Euphorbiaceous family and the most important member of the genus Hevea. The growth of rubber trees should be considered when making land-use decisions. The conventional way of obtaining this information is time-consuming, expensive, and imposes re...

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Main Author:	Abidin, Nurhidayah
Format:	Thesis
Language:	English
Published:	2022
Subjects:	Remote Sensing Geomatics
Online Access:	https://ir.uitm.edu.my/id/eprint/57081/2/57081.pdf
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id	my-uitm-ir.57081
record_format	uketd_dc
spelling	my-uitm-ir.570812024-06-27T06:56:56Z Detection of rubber tree using image classification and vegetation indices / Nurhidayah Abidin 2022 Abidin, Nurhidayah Remote Sensing Geomatics The rubber tree (Hevea brasiliensis is a tree of the Euphorbiaceous family and the most important member of the genus Hevea. The growth of rubber trees should be considered when making land-use decisions. The conventional way of obtaining this information is time-consuming, expensive, and imposes restrictions on access to certain locations. The information on existing rubber cultivation acreages and tree growth conditions is critical for plantation management functions such as field management planning and decision-making. Therefore, the aim of this study is to detect the rubber trees using image classification and vegetation indices. The objectives of this study were i)to determine land use the accuracy of using supervised classification and ii)to identify the range of vegetation index for rubber trees using NDVI. The method used in this study is by using supervised classification and the use of the method is the maximum possibility. The study identified vegetation indices using NDVI. This study is very important to farmers because it can show the area of rubber trees using remote sensing method as well as to know the concentration of rubber trees area. The result will be demonstrated through an assessment of the accuracy of image classification and production of an NDVI map. 2022 Thesis https://ir.uitm.edu.my/id/eprint/57081/ https://ir.uitm.edu.my/id/eprint/57081/2/57081.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	Remote Sensing Geomatics
spellingShingle	Remote Sensing Geomatics Abidin, Nurhidayah Detection of rubber tree using image classification and vegetation indices / Nurhidayah Abidin
description	The rubber tree (Hevea brasiliensis is a tree of the Euphorbiaceous family and the most important member of the genus Hevea. The growth of rubber trees should be considered when making land-use decisions. The conventional way of obtaining this information is time-consuming, expensive, and imposes restrictions on access to certain locations. The information on existing rubber cultivation acreages and tree growth conditions is critical for plantation management functions such as field management planning and decision-making. Therefore, the aim of this study is to detect the rubber trees using image classification and vegetation indices. The objectives of this study were i)to determine land use the accuracy of using supervised classification and ii)to identify the range of vegetation index for rubber trees using NDVI. The method used in this study is by using supervised classification and the use of the method is the maximum possibility. The study identified vegetation indices using NDVI. This study is very important to farmers because it can show the area of rubber trees using remote sensing method as well as to know the concentration of rubber trees area. The result will be demonstrated through an assessment of the accuracy of image classification and production of an NDVI map.
format	Thesis
qualification_level	Bachelor degree
author	Abidin, Nurhidayah
author_facet	Abidin, Nurhidayah
author_sort	Abidin, Nurhidayah
title	Detection of rubber tree using image classification and vegetation indices / Nurhidayah Abidin
title_short	Detection of rubber tree using image classification and vegetation indices / Nurhidayah Abidin
title_full	Detection of rubber tree using image classification and vegetation indices / Nurhidayah Abidin
title_fullStr	Detection of rubber tree using image classification and vegetation indices / Nurhidayah Abidin
title_full_unstemmed	Detection of rubber tree using image classification and vegetation indices / Nurhidayah Abidin
title_sort	detection of rubber tree using image classification and vegetation indices / nurhidayah abidin
granting_institution	Universiti Teknologi MARA, Perlis
granting_department	Faculty of Architecture, Planning and Surveying
publishDate	2022
url	https://ir.uitm.edu.my/id/eprint/57081/2/57081.pdf
_version_	1804889639767506944

Detection of rubber tree using image classification and vegetation indices / Nurhidayah Abidin

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