An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani

Urban growth classification categorized cities development according to its expansion forms. The forms of urban growth can be simulated using satellite remote sensing data and suitable classification technique. Due to limited information on the characteristics of urban expansion especially in develo...

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Main Author:	Ab Ghani, Nur Laila
Format:	Thesis
Language:	English
Published:	2015
Subjects:	Urban renewal Urban redevelopment
Online Access:	https://ir.uitm.edu.my/id/eprint/14269/1/TM_NUR%20LAILA%20AB%20GHANI%20CS%2015_5.pdf
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id	my-uitm-ir.14269
record_format	uketd_dc
spelling	my-uitm-ir.142692022-04-18T04:49:43Z An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani 2015-01 Ab Ghani, Nur Laila Urban renewal. Urban redevelopment Urbanization. City and country Evolutionary programming (Computer science). Genetic algorithms Urban growth classification categorized cities development according to its expansion forms. The forms of urban growth can be simulated using satellite remote sensing data and suitable classification technique. Due to limited information on the characteristics of urban expansion especially in developing countries, an urban growth classification model is required for urban growth analysis. Although extensive research has been carried out into urban growth classification, further research must focus on the improvement of classification algorithms since researchers are concerned about the limitation of existing classification algorithms that may produce incorrect classification results. This research is mainly about improving existing classification algorithms for a correct classification results and evaluating the accuracy of classification algorithms in correctly determining urban growth forms, The datasets are Landsat Thematic Mapper (TM) images of Klang Valley, one of the most rapid urban growth areas in Malaysia. In order to fulfil the research goal, the datasets are pre-processed into binary images containing the developed and undeveloped portion of the study area. The new urban areas identified from the binary images are classified to their urban growth forms using moving window, topological relation border length and landscape expansion index algorithms. The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. The results are evaluated by receiver operating characteristic (ROC) graph and the existing technique that gives the best performance is landscape expansion index. An accurate urban expansion map helps town planners in planning land use allocation and identifying potential land area to be developed 2015-01 Thesis https://ir.uitm.edu.my/id/eprint/14269/ https://ir.uitm.edu.my/id/eprint/14269/1/TM_NUR%20LAILA%20AB%20GHANI%20CS%2015_5.pdf text en public mphil masters Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences Zainal Abidin, Siti Zaleha (Assoc. Prof. Dr.) Abd Khalid, Noor Elaiza (Dr.)
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Zainal Abidin, Siti Zaleha (Assoc. Prof. Dr.) Abd Khalid, Noor Elaiza (Dr.)
topic	Urban renewal Urban redevelopment Urban renewal Urban redevelopment Urban renewal Urban redevelopment
spellingShingle	Urban renewal Urban redevelopment Urban renewal Urban redevelopment Urban renewal Urban redevelopment Ab Ghani, Nur Laila An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
description	Urban growth classification categorized cities development according to its expansion forms. The forms of urban growth can be simulated using satellite remote sensing data and suitable classification technique. Due to limited information on the characteristics of urban expansion especially in developing countries, an urban growth classification model is required for urban growth analysis. Although extensive research has been carried out into urban growth classification, further research must focus on the improvement of classification algorithms since researchers are concerned about the limitation of existing classification algorithms that may produce incorrect classification results. This research is mainly about improving existing classification algorithms for a correct classification results and evaluating the accuracy of classification algorithms in correctly determining urban growth forms, The datasets are Landsat Thematic Mapper (TM) images of Klang Valley, one of the most rapid urban growth areas in Malaysia. In order to fulfil the research goal, the datasets are pre-processed into binary images containing the developed and undeveloped portion of the study area. The new urban areas identified from the binary images are classified to their urban growth forms using moving window, topological relation border length and landscape expansion index algorithms. The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. The results are evaluated by receiver operating characteristic (ROC) graph and the existing technique that gives the best performance is landscape expansion index. An accurate urban expansion map helps town planners in planning land use allocation and identifying potential land area to be developed
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Ab Ghani, Nur Laila
author_facet	Ab Ghani, Nur Laila
author_sort	Ab Ghani, Nur Laila
title	An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
title_short	An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
title_full	An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
title_fullStr	An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
title_full_unstemmed	An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
title_sort	improved pixel-based and region-based approach for urban growth classification algorithms / nur laila ab ghani
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2015
url	https://ir.uitm.edu.my/id/eprint/14269/1/TM_NUR%20LAILA%20AB%20GHANI%20CS%2015_5.pdf
_version_	1783733242439925760

An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani

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