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 Urbanization. City and country Evolutionary programming (Computer science). Genetic algorithms
Online Access:	http://ir.uitm.edu.my/id/eprint/14269/ http://ir.uitm.edu.my/id/eprint/14269/1/TM_NUR%20LAILA%20AB%20GHANI%20CS%2015_5.pdf

id	uitm-14269
recordtype	eprints
spelling	uitm-142692016-08-19T01:55:28Z http://ir.uitm.edu.my/id/eprint/14269/ An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani 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 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/14269/1/TM_NUR%20LAILA%20AB%20GHANI%20CS%2015_5.pdf Ab Ghani, Nur Laila (2015) An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani. Masters thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Urban renewal. Urban redevelopment Urbanization. City and country Evolutionary programming (Computer science). Genetic algorithms
spellingShingle	Urban renewal. Urban redevelopment Urbanization. City and country Evolutionary programming (Computer science). Genetic algorithms 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
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
publishDate	2015
url	http://ir.uitm.edu.my/id/eprint/14269/ http://ir.uitm.edu.my/id/eprint/14269/1/TM_NUR%20LAILA%20AB%20GHANI%20CS%2015_5.pdf
first_indexed	2023-09-18T22:51:15Z
last_indexed	2023-09-18T22:51:15Z
_version_	1777417558783164416

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

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