Comparison between object based classfication and pixel based classfication technique to detect deforestation in Ulu Muda forest reserve, Kedah / Shahrul Nizam Jamaludin

Remote sensing is moving toward mapping the Earth surface using the highly technology implement. The researcher has invented two types of classification that can be integrated with the modern technology. Those categories of classifications are pixel based classification and object based classific...

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Main Author:	Jamaludin, Shahrul Nizam
Format:	Thesis
Language:	English
Published:	2018
Subjects:	SD Forestry Remote sensing
Online Access:	https://ir.uitm.edu.my/id/eprint/21774/1/TD_SHAHRUL%20NIZAM%20JAMALUDIN%20AP%20R%2018_5.pdf
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id	my-uitm-ir.21774
record_format	uketd_dc
spelling	my-uitm-ir.217742018-10-11T07:53:36Z Comparison between object based classfication and pixel based classfication technique to detect deforestation in Ulu Muda forest reserve, Kedah / Shahrul Nizam Jamaludin 2018-10-05 Jamaludin, Shahrul Nizam SD Forestry Remote sensing Remote sensing is moving toward mapping the Earth surface using the highly technology implement. The researcher has invented two types of classification that can be integrated with the modern technology. Those categories of classifications are pixel based classification and object based classification. Both methods purpose to analyse forest cover and changes especially deforestation activity but, due to the early stage of these methods, their abilities to classify land cover and monitor forest dynamics have not fully evaluated and investigate. Here, the strength for both methods was studied, to know which one is the best in detecting deforestation at Ulu Muda Forest Reserve, Kedah. The forest cover at Ulu Muda will be classified, where pixel based classification was done using the Erdas software while object based classification completed using the eCognition software. Satellite imagery from SPOT 5 and 6 with size pixel of 12 metre and 7 metre were used in change detection analysis. The accuracy assessment has been done to identify the overall accuracy of for both classifications including the user and producer accuracy. The higher value of that accuracy approaching to 100, the more accurate the classification can be said. The possible best method of classification in detecting deforestation activity will be determined and explained more its concept in this study. 2018-10 Thesis https://ir.uitm.edu.my/id/eprint/21774/ https://ir.uitm.edu.my/id/eprint/21774/1/TD_SHAHRUL%20NIZAM%20JAMALUDIN%20AP%20R%2018_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	SD Forestry Remote sensing
spellingShingle	SD Forestry Remote sensing Jamaludin, Shahrul Nizam Comparison between object based classfication and pixel based classfication technique to detect deforestation in Ulu Muda forest reserve, Kedah / Shahrul Nizam Jamaludin
description	Remote sensing is moving toward mapping the Earth surface using the highly technology implement. The researcher has invented two types of classification that can be integrated with the modern technology. Those categories of classifications are pixel based classification and object based classification. Both methods purpose to analyse forest cover and changes especially deforestation activity but, due to the early stage of these methods, their abilities to classify land cover and monitor forest dynamics have not fully evaluated and investigate. Here, the strength for both methods was studied, to know which one is the best in detecting deforestation at Ulu Muda Forest Reserve, Kedah. The forest cover at Ulu Muda will be classified, where pixel based classification was done using the Erdas software while object based classification completed using the eCognition software. Satellite imagery from SPOT 5 and 6 with size pixel of 12 metre and 7 metre were used in change detection analysis. The accuracy assessment has been done to identify the overall accuracy of for both classifications including the user and producer accuracy. The higher value of that accuracy approaching to 100, the more accurate the classification can be said. The possible best method of classification in detecting deforestation activity will be determined and explained more its concept in this study.
format	Thesis
qualification_level	Bachelor degree
author	Jamaludin, Shahrul Nizam
author_facet	Jamaludin, Shahrul Nizam
author_sort	Jamaludin, Shahrul Nizam
title	Comparison between object based classfication and pixel based classfication technique to detect deforestation in Ulu Muda forest reserve, Kedah / Shahrul Nizam Jamaludin
title_short	Comparison between object based classfication and pixel based classfication technique to detect deforestation in Ulu Muda forest reserve, Kedah / Shahrul Nizam Jamaludin
title_full	Comparison between object based classfication and pixel based classfication technique to detect deforestation in Ulu Muda forest reserve, Kedah / Shahrul Nizam Jamaludin
title_fullStr	Comparison between object based classfication and pixel based classfication technique to detect deforestation in Ulu Muda forest reserve, Kedah / Shahrul Nizam Jamaludin
title_full_unstemmed	Comparison between object based classfication and pixel based classfication technique to detect deforestation in Ulu Muda forest reserve, Kedah / Shahrul Nizam Jamaludin
title_sort	comparison between object based classfication and pixel based classfication technique to detect deforestation in ulu muda forest reserve, kedah / shahrul nizam jamaludin
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Architecture, Planning and Surveying
publishDate	2018
url	https://ir.uitm.edu.my/id/eprint/21774/1/TD_SHAHRUL%20NIZAM%20JAMALUDIN%20AP%20R%2018_5.pdf
_version_	1783733772694323200

Comparison between object based classfication and pixel based classfication technique to detect deforestation in Ulu Muda forest reserve, Kedah / Shahrul Nizam Jamaludin

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