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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
https://ir.uitm.edu.my/id/eprint/57081/
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spelling my.uitm.ir.570812024-06-27T06:56:56Z https://ir.uitm.edu.my/id/eprint/57081/ Detection of rubber tree using image classification and vegetation indices / Nurhidayah Abidin 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 NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/57081/2/57081.pdf Detection of rubber tree using image classification and vegetation indices / Nurhidayah Abidin. (2022) Degree thesis, thesis, Universiti Teknologi MARA, Perlis. <http://terminalib.uitm.edu.my/57081.pdf>
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
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
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
publishDate 2022
url https://ir.uitm.edu.my/id/eprint/57081/2/57081.pdf
https://ir.uitm.edu.my/id/eprint/57081/
_version_ 1803339455708266496
score 13.211869

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