Accuracy assessment of automation oil palm tree counting using ecognition based of UAV imagery / Fairuz Maizan Sazeli

A good management of oil palm plantation become a growing concern as the demand on oil palm is increasing. The farmers need a high technological system that can make it easier to identify the number of oil palm in the plantation for the fertilizers and prediction of yield. There is already manual...

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Main Author:	Sazeli, Fairuz Maizan
Format:	Thesis
Language:	English
Published:	2019
Subjects:	Global Positioning System Geographic information systems
Online Access:	https://ir.uitm.edu.my/id/eprint/24511/1/TD_FAIRUZ%20MAIZAN%20SAZELI%20AP%20R%2019_5.PDF
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id	my-uitm-ir.24511
record_format	uketd_dc
spelling	my-uitm-ir.245112019-06-20T04:27:03Z Accuracy assessment of automation oil palm tree counting using ecognition based of UAV imagery / Fairuz Maizan Sazeli 2019-06-20 Sazeli, Fairuz Maizan Global Positioning System Geographic information systems Large farms. Plantations A good management of oil palm plantation become a growing concern as the demand on oil palm is increasing. The farmers need a high technological system that can make it easier to identify the number of oil palm in the plantation for the fertilizers and prediction of yield. There is already manual technique and automation technique in determining the number of oil palm trees exist but the manual technique is time consuming and more expensive. The existence of automation method has not been widely known by the farmers and the accuracy is not yet been verified. Therefore, the accuracy of automation technique should be verified as it can be beneficial to the agriculture sector. This research aim is to identify the accuracy of automation method in oil palm tree counting by using the result from manual digitizing as a verification subject to the automation technique. The data used in this research which is UAV imagery data has been obtained from Braintree company. This data is suitable to be used in this project as it provides high spatial resolution where the trees can be identified easily. The result analyzes whether the accuracy of automation method by manipulating five different threshold values approximately same as the accuracy of manual method. It is suggested that the result of one of the threshold value in the automation method has a high accuracy and can be used for oil palm tree counting. 2019-06 Thesis https://ir.uitm.edu.my/id/eprint/24511/ https://ir.uitm.edu.my/id/eprint/24511/1/TD_FAIRUZ%20MAIZAN%20SAZELI%20AP%20R%2019_5.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	Global Positioning System Geographic information systems Global Positioning System
spellingShingle	Global Positioning System Geographic information systems Global Positioning System Sazeli, Fairuz Maizan Accuracy assessment of automation oil palm tree counting using ecognition based of UAV imagery / Fairuz Maizan Sazeli
description	A good management of oil palm plantation become a growing concern as the demand on oil palm is increasing. The farmers need a high technological system that can make it easier to identify the number of oil palm in the plantation for the fertilizers and prediction of yield. There is already manual technique and automation technique in determining the number of oil palm trees exist but the manual technique is time consuming and more expensive. The existence of automation method has not been widely known by the farmers and the accuracy is not yet been verified. Therefore, the accuracy of automation technique should be verified as it can be beneficial to the agriculture sector. This research aim is to identify the accuracy of automation method in oil palm tree counting by using the result from manual digitizing as a verification subject to the automation technique. The data used in this research which is UAV imagery data has been obtained from Braintree company. This data is suitable to be used in this project as it provides high spatial resolution where the trees can be identified easily. The result analyzes whether the accuracy of automation method by manipulating five different threshold values approximately same as the accuracy of manual method. It is suggested that the result of one of the threshold value in the automation method has a high accuracy and can be used for oil palm tree counting.
format	Thesis
qualification_level	Bachelor degree
author	Sazeli, Fairuz Maizan
author_facet	Sazeli, Fairuz Maizan
author_sort	Sazeli, Fairuz Maizan
title	Accuracy assessment of automation oil palm tree counting using ecognition based of UAV imagery / Fairuz Maizan Sazeli
title_short	Accuracy assessment of automation oil palm tree counting using ecognition based of UAV imagery / Fairuz Maizan Sazeli
title_full	Accuracy assessment of automation oil palm tree counting using ecognition based of UAV imagery / Fairuz Maizan Sazeli
title_fullStr	Accuracy assessment of automation oil palm tree counting using ecognition based of UAV imagery / Fairuz Maizan Sazeli
title_full_unstemmed	Accuracy assessment of automation oil palm tree counting using ecognition based of UAV imagery / Fairuz Maizan Sazeli
title_sort	accuracy assessment of automation oil palm tree counting using ecognition based of uav imagery / fairuz maizan sazeli
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Architecture, Planning and Surveying
publishDate	2019
url	https://ir.uitm.edu.my/id/eprint/24511/1/TD_FAIRUZ%20MAIZAN%20SAZELI%20AP%20R%2019_5.PDF
_version_	1783733847654924288

Accuracy assessment of automation oil palm tree counting using ecognition based of UAV imagery / Fairuz Maizan Sazeli

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