Cellular automata based temporal process understanding of urban growth

Cheng, J and Masser, I (2002) Cellular automata based temporal process understanding of urban growth. Lecture Notes in Computer Science, 2493. pp. 325-337. ISSN 0302-9743

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Official URL: https://link.springer.com/bookseries/558

Abstract

Understanding of urban growth process is highly crucial in making development plan and sustainable growth management policy. As the process involves multi-actors, multi-behavior and various policies, it is endowed with unpredictable spatial and temporal complexities, it requires the occurrence of new simulation approach, which is process-oriented and has stronger capacities of interpretation. In this paper, A cellular automata-based model is designed for understanding the temporal process of urban growth by incorporating dynamic weighting concept and project-based approach. We argue that this methodology is able to interpret and visualize the dynamic process more temporally and transparently.

Item Type:	Article
Peer-reviewed:	Yes
Date Deposited:	24 May 2017 08:41
Publisher:	Springer
Additional Information:	This is an Author Accepted Manuscript of a paper accepted for publication in Lecture Notes in Computer Science, published by and copyright Springer.
Divisions:	Faculties > Science and Engineering
Subject terms:	08 Information And Computing Sciences, Artificial Intelligence & Image Processing
URI:	https://e-space.mmu.ac.uk/id/eprint/618456
DOI:	https://doi.org/10.1007/3-540-45830-1_31
ISSN	0302-9743

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