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

Abstract

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 CO 2 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.

Land use optimization through bridging multiobjective optimization and multicriteria decision‐making models (case study: Tilabad Watershed, Golestan Province, Iran)

“…The research carried out in the field of land use optimization are divided into three categories of linear programming models (LP) (Benli & Kodal, 2003; Hongrui et al, 2010; Min et al, 2015; Nikkami et al, 2009; Owji, Nikkami, Mahdian, et al, 2012; Sadeghi et al, 2009; Sokouti & Nikkami, 2017; Sunandar et al, 2014; Vafakhah & Mohseni Saravi, 2011), Cellular Automata (CA) models (Li & Yeh, 2002), and models based on intelligent algorithms, and evolutionary and innovative methods (Cao et al,2012; Datta et al, 2007; García et al, 2017; Lazoglou et al, 2016; Y. Liu et al, 2013, 2015; Mohammadi et al, 2015; Shaygan et al, 2014; Yuan et al, 2014; H. Zhang et al, 2016; H. H. Zhang et al, 2010). In LP models, the optimal land use structure is identified rapidly based on the accurate mathematical definition of limits and one objective function (Aerts et al, 2003).…”

“…The non‐dominated sorting genetic algorithm II (NSGA II) evolutionary algorithm, as an optimization and genetic algorithm (Horn et al, 1999), is considered to be one of the most efficient and widely used multiobjective evolutionary algorithms. This algorithm does not require any additional parameters and has a high calculation speed (Deb et al, 2002), so it has been widely used in land use optimization and spatial planning (Cao et al, 2011; Datta et al, 2007; García et al,2017; Hojjati et al, 2018; Lazoglou et al, 2016; Y. Liu et al, 2013; Mohammadi et al, 2015; Noor et al, 2016; Shaygan et al, 2014). However, this algorithm generates a set of nondominant solutions from which the selection of a unique solution becomes questionable for decision‐makers.…”

Environmentally Sound Spatial Management Using Conservation and Land Evaluation Approach at Sloping Lands in Humid Tropic (A case study of Antang Kalang sub-district, Central Kalimantan, Indonesia)

“…Appropriate land-use planning is then required in order to achieve long-term sustained yields involving the successful management of resources for agricultural lands to satisfy changing human needs while maintaining and enhancing the quality of the environment and conserving natural resources (Hoffman, 2017;Altieri, 1992). Planning is underpinned by the assumption that adequate information exists for those exercising public authority to make decisions regarding the best use of land in the future (Flaherty & Smit, 1982) and is concerned with sustainable land-use allocation (Garcia et al, 2017) and it must be based on an understanding both of the natural environment and of the kinds of land-use envisaged (FAO, 1976). The function of landuse planning for agricultural purposes is, therefore, to guide decisions on land-use in such way that the resources of environment are put to the most beneficial use, while at the same time conserving those resources for the future.…”

Optimization of County-Level Land Resource Allocation through the Improvement of Allocation Efficiency from the Perspective of Sustainable Development

“…The overexpansion of construction land may have negative effects on food security and ecological security, which threatens sustainable development, and excessive protection of agricultural land may restrict the development of regional economies. Therefore, in order to balance survival needs [5,6] and economic development, the only way to alleviate the imbalance between supply and demand of land resources and realize efficient utilization of land is to constantly regulate and optimize regional land resource allocation between agricultural and nonagricultural sectors and to coordinate regional land resource utilization [7,8,9,10].…”