Spatio‐temporal land use multi‐objective optimization: A case study in Central China

Abstract

Much effort has been applied to the study of land use multi‐objective optimization. However, most of these studies have focused on the final land use scenarios in the projected year, without considering how to reach the final optimized land use scenario. To fill this gap, a spatio‐temporal land use multi‐objective optimization (STLU‐MOO) model is innovatively proposed in this research to determine possible spatial land use solutions over time. The STLU‐MOO is an extension of a genetic land use multi‐objective optimization model (LU‐MOO) in which the LU‐MOO is generally carried out in different years, and the solutions at year T will affect the solutions at year T + 1. We used the Wuhan agglomeration (WHA) as our case study area. The STLU‐MOO model was employed separately for the nine cities in the WHA, and social, economic, and environmental objectives have been considered. The success of the experiments in the case study demonstrated the value and novelty of our proposed STLU‐MOO model. In addition, the results also indicated that the objectives considered in the case study were in conflict. According to the results, the optimal land use plan in 2050 can be traced back to 2040, 2030, and 2020, providing a series of Pareto solutions over the years which can provide spatio‐temporal land use multi‐objective optimization solutions to support the land use planning process.

Spatial Multi-Objective Land Use Optimization toward Livability Based on Boundary-Based Genetic Algorithm: A Case Study in Singapore

“…Land use optimization has been broadly studied in the past decades towards various concerns or objectives [5][6][7][8][9][10][11][12][13][14]. However, there has not been many studies specifically on the livability oriented land use optimization except some general discussions and interpretation on livability from various perspectives of researchers.…”

“…Another kind of effective method is the abovementioned "weighted-sum" method. Although it cannot yield non-convex optimal solutions, it has still been commonly used because of its simplicity and effectiveness for most of the multi-objective optimization problems [6,9,36,37]. In this research, the goal programming and weighted-sum methods are used to construct the land use optimization model.…”

Many‐objective land use planning using a hypercube‐based NSGA‐III algorithm

“…Each of these formats has its own advantages and disadvantages. Using the raster format facilitates the definition of the neighborhood, chromosomes encoding, and the application of GA operators because the computations can be conducted on a regular grid (Cao, Zhang, & Wang, 2019; Handayanto, Tripathi, Kim, & Guha, 2017; Mohammadi et al., 2016; Schwaab et al., 2018; Shaygan et al., 2014; Song & Chen, 2018; Stewart et al., 2004). However, the raster format is dependent on the size of grid cells (resolution).…”

“…In specialized and complex problems such as ULUP, in which the objective functions, input data, and problem details have a particular format and do not have a standard form, it is necessary to make significant changes to adapt the algorithms to the problem. Previous researchers (Cao, Zhang, & Wang, 2019; Cao et al, 2011; Masoumi et al, 2017; Masoumi et al, 2020; Schwaab et al, 2018) have shown that in some cases the use of these algorithms in the ULUP problem does not create a diverse and well‐ordered solution space. Therefore, the goal here is to balance the density of the solutions in the PF and to achieve a wider variety of solutions based on the use of the NSGA‐III.…”

Practical Efficient Regional Land-Use Planning Using Constrained Multi-Objective Genetic Algorithm Optimization

“…Among various ecological factors, Ecosystem Services Value (ESV), namely the value of ecosystem service and natural capital estimated by economic rules, is widely used due to its clear scientific significance and ease of calculation [24][25][26]. In addition, Net Primary Productivity (NPP), soil erosion, and pollution control can be chosen if necessary to accord with environmental protection policies [27,28]. For the social benefit measurement, compatibility or incompatibility of land use is most often adopted [29][30][31], while compactness and conflict degree (between neighboring land use localities) are also used for social objectives [3,32,33].…”