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Generating transition rules of Cellular Automata for urban growth prediction / Nur Laila Ab Ghani

Urban growth prediction can be simulated using digital maps. The growth of a non built area can be detected through the change of pixels in a temporal imagery data. A built area usually affects the growth of its surrounding area as similar to Cellular Automata theory. This project is mainly about ob...

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Main Author: Ab Ghani, Nur Laila
Format: Thesis
Language:English
Published: 2010
Online Access:https://ir.uitm.edu.my/id/eprint/64103/1/64103.PDF
https://ir.uitm.edu.my/id/eprint/64103/
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spelling my.uitm.ir.641032023-08-29T09:17:54Z https://ir.uitm.edu.my/id/eprint/64103/ Generating transition rules of Cellular Automata for urban growth prediction / Nur Laila Ab Ghani Ab Ghani, Nur Laila Urban growth prediction can be simulated using digital maps. The growth of a non built area can be detected through the change of pixels in a temporal imagery data. A built area usually affects the growth of its surrounding area as similar to Cellular Automata theory. This project is mainly about obtaining a set of transition rules to detect the pattern of urban growth for neighbor hood cells. As a case study, five satellite images of Subang Jaya district are used. In order to generate the transition rules, a unique pattern or surrounding cells are identified. The transition rules are implemented using a testing engine to test the accuracy. The better accuracy leads to better monitoring system to cater future leavings. 2010 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/64103/1/64103.PDF Generating transition rules of Cellular Automata for urban growth prediction / Nur Laila Ab Ghani. (2010) Degree thesis, thesis, Universiti Teknologi MARA (UiTM).
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
description Urban growth prediction can be simulated using digital maps. The growth of a non built area can be detected through the change of pixels in a temporal imagery data. A built area usually affects the growth of its surrounding area as similar to Cellular Automata theory. This project is mainly about obtaining a set of transition rules to detect the pattern of urban growth for neighbor hood cells. As a case study, five satellite images of Subang Jaya district are used. In order to generate the transition rules, a unique pattern or surrounding cells are identified. The transition rules are implemented using a testing engine to test the accuracy. The better accuracy leads to better monitoring system to cater future leavings.
format Thesis
author Ab Ghani, Nur Laila
spellingShingle Ab Ghani, Nur Laila
Generating transition rules of Cellular Automata for urban growth prediction / Nur Laila Ab Ghani
author_facet Ab Ghani, Nur Laila
author_sort Ab Ghani, Nur Laila
title Generating transition rules of Cellular Automata for urban growth prediction / Nur Laila Ab Ghani
title_short Generating transition rules of Cellular Automata for urban growth prediction / Nur Laila Ab Ghani
title_full Generating transition rules of Cellular Automata for urban growth prediction / Nur Laila Ab Ghani
title_fullStr Generating transition rules of Cellular Automata for urban growth prediction / Nur Laila Ab Ghani
title_full_unstemmed Generating transition rules of Cellular Automata for urban growth prediction / Nur Laila Ab Ghani
title_sort generating transition rules of cellular automata for urban growth prediction / nur laila ab ghani
publishDate 2010
url https://ir.uitm.edu.my/id/eprint/64103/1/64103.PDF
https://ir.uitm.edu.my/id/eprint/64103/
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score 13.160551

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