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

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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