Optimization of oil palm age recognition using Sentinel -2A and Landsat-8 / Nurul Nadia Zainuleden

Oil palm (Elaeis guineensis) trees have made significant contributions to Southeast Asia recent economic development. Malaysia has made significant strides in the oil palm industry. It began as an ornamental plant in Malaysia and has since grown into a multibillion-dollar industry. It has the highes...

Full description

Saved in:

Bibliographic Details
Main Author:	Zainuleden, Nurul Nadia
Format:	Thesis
Language:	English
Published:	2022
Subjects:	Aerial geography Field crops
Online Access:	https://ir.uitm.edu.my/id/eprint/70056/1/70056.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uitm-ir.70056
record_format	uketd_dc
spelling	my-uitm-ir.700562023-05-19T09:12:23Z Optimization of oil palm age recognition using Sentinel -2A and Landsat-8 / Nurul Nadia Zainuleden 2022 Zainuleden, Nurul Nadia Aerial geography Field crops Oil palm (Elaeis guineensis) trees have made significant contributions to Southeast Asia recent economic development. Malaysia has made significant strides in the oil palm industry. It began as an ornamental plant in Malaysia and has since grown into a multibillion-dollar industry. It has the highest global demand as an ingredient in food, cosmetics, animal feed, bioenergy, and other products. Malaysia currently ranks second in palm oil production after Indonesia, accounting for 39 percent of global production and 44 percent of palm oil exports. Thus, Malaysia has an important role to play in achieving the growing global demand for oils and fats because it is a major producer and exporter of palm oil and palm oil products. The purpose of this study is to identify the parameter and characteristic of the age of oil palm based on literature research as well to quantify the oil palm trees based on age distribution derived from satellite and UAV imagery and to compare both Sentinel - 2 and Landsat 8 imagery in their efficiency of age recognition for oil palm trees towards crown diameter extraction from UAV imagery. The satellite images were used are Sentinel-2, Landsat 8, and Unmanned Aerial Vehicle (UAV) dataset imagery were used on the same year in 2018. The process used two methods which are Remote Sensing techniques and Geographic Integration System (GIS) in monitoring and detecting oil palm plantations to maximise productivity. The study outcome is a map distribution of oil palm age and Normalized Differences Index Vegetation (NDVI) in the study area. 2022 Thesis https://ir.uitm.edu.my/id/eprint/70056/ https://ir.uitm.edu.my/id/eprint/70056/1/70056.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 Field crops
spellingShingle	Aerial geography Field crops Zainuleden, Nurul Nadia Optimization of oil palm age recognition using Sentinel -2A and Landsat-8 / Nurul Nadia Zainuleden
description	Oil palm (Elaeis guineensis) trees have made significant contributions to Southeast Asia recent economic development. Malaysia has made significant strides in the oil palm industry. It began as an ornamental plant in Malaysia and has since grown into a multibillion-dollar industry. It has the highest global demand as an ingredient in food, cosmetics, animal feed, bioenergy, and other products. Malaysia currently ranks second in palm oil production after Indonesia, accounting for 39 percent of global production and 44 percent of palm oil exports. Thus, Malaysia has an important role to play in achieving the growing global demand for oils and fats because it is a major producer and exporter of palm oil and palm oil products. The purpose of this study is to identify the parameter and characteristic of the age of oil palm based on literature research as well to quantify the oil palm trees based on age distribution derived from satellite and UAV imagery and to compare both Sentinel - 2 and Landsat 8 imagery in their efficiency of age recognition for oil palm trees towards crown diameter extraction from UAV imagery. The satellite images were used are Sentinel-2, Landsat 8, and Unmanned Aerial Vehicle (UAV) dataset imagery were used on the same year in 2018. The process used two methods which are Remote Sensing techniques and Geographic Integration System (GIS) in monitoring and detecting oil palm plantations to maximise productivity. The study outcome is a map distribution of oil palm age and Normalized Differences Index Vegetation (NDVI) in the study area.
format	Thesis
qualification_level	Bachelor degree
author	Zainuleden, Nurul Nadia
author_facet	Zainuleden, Nurul Nadia
author_sort	Zainuleden, Nurul Nadia
title	Optimization of oil palm age recognition using Sentinel -2A and Landsat-8 / Nurul Nadia Zainuleden
title_short	Optimization of oil palm age recognition using Sentinel -2A and Landsat-8 / Nurul Nadia Zainuleden
title_full	Optimization of oil palm age recognition using Sentinel -2A and Landsat-8 / Nurul Nadia Zainuleden
title_fullStr	Optimization of oil palm age recognition using Sentinel -2A and Landsat-8 / Nurul Nadia Zainuleden
title_full_unstemmed	Optimization of oil palm age recognition using Sentinel -2A and Landsat-8 / Nurul Nadia Zainuleden
title_sort	optimization of oil palm age recognition using sentinel -2a and landsat-8 / nurul nadia zainuleden
granting_institution	Universiti Teknologi MARA, Perlis
granting_department	Faculty of Architecture Planning and Surveying
publishDate	2022
url	https://ir.uitm.edu.my/id/eprint/70056/1/70056.pdf
_version_	1783735923315310592

Optimization of oil palm age recognition using Sentinel -2A and Landsat-8 / Nurul Nadia Zainuleden

Similar Items