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...
Saved in:
| Main Author: | |
|---|---|
| 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/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|