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Sustainability 2017, 9(6), 927; doi:10.3390/su9060927

Multi-Objective Spatial Optimization: Sustainable Land Use Allocation at Sub-Regional Scale

1
Department of Agronomy, University of Cordoba, Rabanales Campus. Ed. 14071 Córdoba, Spain
2
Freelance consultant in computing languages, Cordillera Central 2428, Fraccionamiento Maravillas Puebla Pue Z.C. 72220, Mexico
3
Gregor Mendel, Z.C. 14071 Córdoba, Spain
*
Author to whom correspondence should be addressed.
Received: 16 February 2017 / Revised: 24 May 2017 / Accepted: 25 May 2017 / Published: 1 June 2017
(This article belongs to the Section Sustainable Use of the Environment and Resources)
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Abstract

The rational use of territorial resources is a key factor in achieving sustainability. Spatial planning is an important tool that helps decision makers to achieve sustainability in the long term. This work proposes a multi-objective model for sustainable land use allocation known as MAUSS (Spanish acronym for “Modelo de Asignación de Uso Sostenible de Suelo”) The model was applied to the Plains of San Juan, Puebla, Mexico, which is currently undergoing a rapid industrialization process. The main objective of the model is to generate land use allocations that lead to a territorial balance within regions in three main ways by maximizing income, minimizing negative environmental pressure on water and air through specific evaluations of water use and CO2 emissions, and minimizing food deficit. The non-sorting genetic algorithm II (NSGA-II) is the evolutionary optimization algorithm of MAUSS. NSGA-II has been widely modified through a novel and efficient random initializing operator that enables spatial rationale from the initial solutions, a crossover operator designed to streamline the best genetic information transmission as well as diversity, and two geometric operators, geographic dispersion (GDO) and the proportion (PO), which strengthen spatial rationality. MAUSS provided a more sustainable land use allocation compared to the current land use distribution in terms of higher income, 9% lower global negative pressure on the environment and 5.2% lower food deficit simultaneously. View Full-Text
Keywords: evolutionary algorithm; food deficit; MAUSS model; negative pressure on the environment (NPE); sustainable land uses evolutionary algorithm; food deficit; MAUSS model; negative pressure on the environment (NPE); sustainable land uses
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

García, G.A.; Rosas, E.P.; García-Ferrer, A.; Barrios, P.M. Multi-Objective Spatial Optimization: Sustainable Land Use Allocation at Sub-Regional Scale. Sustainability 2017, 9, 927.

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