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Spatial optimization as a generative technique for sustainable multiobjective land-use allocation

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Abstract:

In this paper, we examine the applicability of spatial optimization as a generative modelling technique for sustainable land-use allocation. Specifically, we test whether spatial optimization can be used to generate a number of compromise spatial alternatives that are both feasible and different from each other. We present a new spatial multiobjective optimization model, which encourages efficient utilization of urban space through infill development, compatibility of adjacent land uses, and defensible redevelopment. The model uses a density-based design constraint developed by the authors. The constraint imposes a predefined level of consistent neighbourhood development to promote contiguity and compactness of urban areas. First, the model is tested on a hypothetical example. Further, we demonstrate a real-world application of the model to land-use planning in Chelan, a small environmental amenity town in the north-central region of the State of Washington, USA. The results indicate that spatial optimization is a promising method for generating land-use alternatives for further consideration in spatial decision-making.

Keywords: Generative modelling; Multiobjective land-use allocation modelling; Spatial optimization; Sustainable land use

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/13658810701587495

Affiliations: 1: Department of Geography, San Diego State University, San Diego, CA 92182-4493, USA,Department of Geography, University of California, Santa Barbara, CA 93106, USA 2: Department of Geography, University of California, Santa Barbara, CA 93106, USA 3: Department of Geography, San Diego State University, San Diego, CA 92182-4493, USA

Publication date: January 1, 2008

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