Comparison of different optimization based land reallocation models

Uyan, Mevlüt; Tongur, Vahit; Ertunç, Ela

doi:10.1016/j.compag.2020.105449

Cited by 19 publications

(9 citation statements)

References 26 publications

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“…Factors such as climate, topography, soil, hydrology, land management conditions, as well as socioeconomic aspects, are often selected [27,28], and a wide range of methods have been developed, including Multi-criterion evaluation (MCE) [29][30][31], analytic hierarchy process (AHP) [32,33], Storie index (SI) [34], rule-based classification method [35,36], etc., for land evaluation. In terms of research methods, the related research has used multi-objective programming model (MOP) [37], cellular automata (CA) [38], comparative advantage index [39], agent-based model (ABM) [40], and multiple optimization algorithms [41][42][43] to optimize land use layout in terms of quantitative structure, spatial pattern, and benefit optimization. However, the planting suitability of food crops and the spatial structure relationship between crops, as well as the reasonable matching of natural and human factors of cultivated land use for different food crops have not received sufficient attention.…”

Section: Introductionmentioning

confidence: 99%

Cultivated Land Use Layout Adjustment Based on Crop Planting Suitability: A Case Study of Typical Counties in Northeast China

Zhang

2021

Land

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Cultivated land use layout adjustment (CLULA) based on crop planting suitability is the refinement and deepening of land use transformation, which is of great significance for optimizing the allocation of cultivated land resources and ensuring food security. At present, people rarely consider the land suitability of crops when using cultivated land, resulting in an imbalance between crop distribution and resource conditions such as water, heat, and soil, and adversely affects the ecological security and utilization efficiency of cultivated land. To alleviate China’s grain planting structural imbalance and efficiency loss, this paper based on the planting suitability of main food crops (rice, soybean, and maize) to adjust and optimize the cultivated land use layout (CLUL) in the typical counties of the main grain production area in Northeast China, using the agent-based model for optimal land allocation (AgentLA) and GIS technology. Findings from the study show that: (1) The planting suitability of rice, soybean, and maize in the region is obviously different. Among them, the suitability level of soybean and maize is high, and that of rice is low. The current CLUL of the food crops needs to be further optimized and adjusted. (2) By optimizing the layout of rice, soybean, and maize, the planting suitability level of the food crops and the concentration level of the CLUL spatial pattern have been improved. (3) The plan for CLULA is formulated: The study area is divided into rice stable production area, maize-soybean rotation area, maize dominant area, and soybean dominant area, and town or village is identified as the implementation unit of CLULA. The plan for CLULA will be conducive to the concentrated farming of food crops according to the suitable natural conditions and management level. The research realized the optimization of spatial structure and cultivated land use patterns of different food crops integrating farming with protecting land. The significance of the study is that it provides a scientific basis and guidance for adjusting the regional planting structure and solving the problem of food structural imbalance.

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Section: Introductionmentioning

confidence: 99%

Cultivated Land Use Layout Adjustment Based on Crop Planting Suitability: A Case Study of Typical Counties in Northeast China

Zhang

2021

Land

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“…Unlike ESV, suitability is an objective with spatial properties that can be used to analyze the ecological status [12]. In addition, compactness is also a spatial objective for allocation to enhance urban intensification and social equality [49,50], which have been shown to be in conflict with suitability objectives [51]. To facilitate the optimization process, the whole region is rasterized into I rows and J columns, with a total of 509 × 417 = 212,253 cells, each with an area of 1 km 2 in size.…”

Section: Land Use Optimization Model Objectivementioning

confidence: 99%

Collaborative Optimal Allocation of Urban Land Guide by Land Ecological Suitability: A Case Study of Guangdong–Hong Kong–Macao Greater Bay Area

Pan

Yan

2023

Land

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Urban land optimization in urban agglomerations plays an important role in promoting territorial spatial planning to achieve high-quality development, land ecological suitability (LES) is one of the important variables influencing its urbanization and needs to be considered in urban growth simulation and modeling. This research proposed a multi-objective urban land optimization (MULO) model based on the non-dominated sorting genetic algorithm II (NSGA-II) which integrates the LES assessment. MULO starts with LES analysis based on a fuzzy analytical hierarchy process (AHP) and a minimum cumulative resistance (MCR) model. Then, two-step linear regression is used to optimize the quantity structure of built-up land. Finally, suitability and compactness are assigned to NSGA-II as objectives to obtain optimal spatial patterns. Taking the example of the Guangdong–Hong Kong–Macao Greater Bay Area, we found that all the newly added built-up land in 2030 is distributed in peri-urban areas around the original settlements, with approximate clustering in the northern part of Guangzhou and the southern part of Foshan under a balanced development scenario. This study highlights the importance of LES in urban growth modeling, and MULO can provide effective support for the spatial planning of urban agglomerations.

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“…The results were found to be useful and acceptable according to interviews with farmers. Furthermore, artificial intelligence-based optimization algorithms have recently been developed, including fuzzy logic (Cay & Iscan, 2011;Ertunç et al, 2018), analytical hierarchy (Cay & Uyan, 2013), genetic algorithm (Akkus et al, 2012;Haklı et al, 2016Haklı et al, , 2018, and migrating birds/simulated annealing (Uyan et al, 2020), which can apply both stages of block-reallocation separately or together. Moreover, a model based on the ABC algorithm, which was designed to be a powerful tool for nonlinear and complex problems in a land reallocation project, was proposed for the first time ( _ Inceyol & Özbeyaz, 2016).…”

Section: Recent Workmentioning

confidence: 99%

A novel preference‐based artificial‐bee‐colony algorithm approach to the land reallocation optimization problem in a land consolidation case study: DOT village in Turkey

Özbeyaz

İnceyol

2023

Expert Systems

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Land consolidation (LC) is a widely used spatial land management tool. The most essential stage of the LC process is land reallocation, which comprises the exchange of property rights. For this reason, land reallocation may be a potential source of dissatisfaction among farmers, and thus, optimization techniques are continually being developed to minimize these dissatisfactions. The goal of this study was to develop a novel preference‐based artificial‐bee‐colony (ABC) algorithm for use in the land reallocation project for DOT village. In the study, the farmer preferences were prioritized. Specifically, 70% of the lands were preference‐based, with the remainder being random. Furthermore, the ABC algorithm's performance was assessed using three limit parameter (LP) values and two probability functions. The best success was attained when the LP was set to 50 and the roulette‐wheel probability function was employed. The success of land reallocation was defined by the occupancy rate in the blocks and the reallocation rates based on the preferences of the farmer's lands. The occupancy rate in all the blocks using the ABC algorithm was 95.54%, the full occupancy rate of blocks according to farmer preferences was 38%, and the land reallocation rate based on the farmers' preferences was 73%. The remaining lands were distributed to the block areas at random using the ABC method. Moreover, the success of the preference‐based population surpassed that of randomly formed populations.

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Comparison of different optimization based land reallocation models

Cited by 19 publications

References 26 publications

Cultivated Land Use Layout Adjustment Based on Crop Planting Suitability: A Case Study of Typical Counties in Northeast China

Cultivated Land Use Layout Adjustment Based on Crop Planting Suitability: A Case Study of Typical Counties in Northeast China

Collaborative Optimal Allocation of Urban Land Guide by Land Ecological Suitability: A Case Study of Guangdong–Hong Kong–Macao Greater Bay Area

A novel preference‐based artificial‐bee‐colony algorithm approach to the land reallocation optimization problem in a land consolidation case study: DOT village in Turkey

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