Ab Ghani, Nur Laila
(2010)
Generating transition rules of Cellular Automata for urban growth prediction / Nur Laila Ab Ghani.
Degree thesis, Universiti Teknologi MARA (UiTM).
Abstract
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.
Metadata
Item Type: | Thesis (Degree) |
---|---|
Creators: | Creators Email / ID Num. Ab Ghani, Nur Laila UNSPECIFIED |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Zainal Abidin, Siti Zaleha (Assoc. Prof. Dr.) UNSPECIFIED |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences |
Programme: | Bachelor Of Computer Science (HONS) |
Keywords: | Digital, Theory, Cellular |
Date: | 2010 |
URI: | https://ir.uitm.edu.my/id/eprint/64103 |
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