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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2010
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my-uitm-ir.641032023-08-29T09:17:54Z Generating transition rules of Cellular Automata for urban growth prediction / Nur Laila Ab Ghani 2010 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 https://ir.uitm.edu.my/id/eprint/64103/ https://ir.uitm.edu.my/id/eprint/64103/1/64103.PDF text en public degree Universiti Teknologi MARA (UiTM) Faculty of Computer and Mathematical Sciences Zainal Abidin, Siti Zaleha (Assoc. Prof. Dr.) |
| institution |
Universiti Teknologi MARA |
| collection |
UiTM Institutional Repository |
| language |
English |
| advisor |
Zainal Abidin, Siti Zaleha (Assoc. Prof. Dr.) |
| 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 |
| qualification_level |
Bachelor degree |
| 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 |
| granting_institution |
Universiti Teknologi MARA (UiTM) |
| granting_department |
Faculty of Computer and Mathematical Sciences |
| publishDate |
2010 |
| url |
https://ir.uitm.edu.my/id/eprint/64103/1/64103.PDF |
| _version_ |
1783735398689669120 |