A segment derived patch-based logistic cellular automata for urban growth modeling with heuristic rules. (September 2017)

• Record Type: Journal Article
• Authors: Li, Xuecao; Gong, Peng; Yu, Le; Hu, Tengyun
• Is Part Of: Computers, environment and urban systems. Volume 65(2017)
• Page Start: 140
• Page End: 149
• Publication Date: 2017-09
• Subjects: Cellular automata -- Patch -- Segmentation -- Landscape -- Urban growth types; City planning -- Data processing -- Periodicals; Regional planning -- Data processing -- Periodicals; 303.4834
• DOI: 10.1016/j.compenvurbsys.2017.06.001
• Languages: English
• ISSNs: 0198-9715

Abstract

Abstract: Cellular automata (CA) models are extensively applied in urban growth modeling in different forms (i.e., pixel or patch). Studies have reported that the patch-based approach can achieve a more realistic urban landscape. However, they are subjected to uncertainties due to a variety of stochastic processes involved, which weakens their effectiveness on urban planning or decision making. Here, we propose a new patch-based urban growth model with heuristic rules that employed logistic CA model with a watershed segmentation algorithm (Segmentation-Patch-CA). The segment objects derived from features of urban CA model were regarded as potential patches for conversion, through defining a utility function that considered both the suitability and heterogeneity of pixels within the patch. Thereafter, two different urban growth types, i.e., organic growth and spontaneous growth, were identified and simulated separately by introducing a landscape expansion index (LEI) that built on neighborhood density analysis. The proposed Segmentation-Patch-CA was applied to Guangzhou City, China. Our results revealed that the proposed model produced a more realistic urban landscape (96.00% and 97.38%) than pixel-based (45.14% and 74.82%) for two modeling periods 2003–2008 and 2008–2012, respectively, when referring to an assembled indicator that closely related to urban patterns (e.g., shape, size, or distribution). Meanwhile, it also achieved a good performance when comparing to other patch-based urban CA models but with less uncertainty. Our model provided a very flexible framework to incorporate patches using segments or self-growth based on pixels, which is very helpful to future urban planning practices. Highlights: Segmentation based on those crucial components of Logistic-CA for model unit generation The converted patches were assessed based on inherent suitability and homogeneity. Two urban growth types (organic and spontaneous) were clearly defined with an indicator. Provided a very flexible framework to integrate two different forms of patch evolution