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http://dx.doi.org/10.3837/tiis.2021.05.005

Zoning Permanent Basic Farmland Based on Artificial Immune System coupling with spatial constraints  

Hua, Wang (Henan Key Laboratory of food safety data intelligence, Zhengzhou University of Light Industry)
Mengyu, Wang (Henan Key Laboratory of food safety data intelligence, Zhengzhou University of Light Industry)
Yuxin, Zhu (Henan Key Laboratory of food safety data intelligence, Zhengzhou University of Light Industry)
Jiqiang, Niu (Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution, Xinyang Normal University)
Xueye, Chen (Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources)
Yang, Zhang (College of Urban Economics and Public Administration, Capital University of Economics and Business)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.15, no.5, 2021 , pp. 1666-1689 More about this Journal
Abstract
The red line of Permanent Basic Farmland is the most important part in the "three-line" demarcation of China's national territorial development plan. The scientific and reasonable delineation of the red line is a major strategic measure being taken by China to improve its ability to safeguard the practical interests of farmers and guarantee national food security. The delineation of Permanent Basic Farmland zoning (DPBFZ) is essentially a multi-objective optimization problem. However, the traditional method of demarcation does not take into account the synergistic development goals of conservation of cultivated land utilization, ecological conservation, or urban expansion. Therefore, this research introduces the idea of artificial immune optimization and proposes a multi-objective model of DPBFZ red line delineation based on a clone selection algorithm. This research proposes an objective functional system consisting of these three sub-objectives: optimal quality of cropland, spatially concentrated distribution, and stability of cropland. It also takes into consideration constraints such as the red line of ecological protection, topography, and space for major development projects. The mathematical formal expressions for the objectives and constraints are given in the paper, and a multi-objective optimal decision model with multiple constraints for the DPBFZ problem is constructed based on the clone selection algorithm. An antibody coding scheme was designed according to the spatial pattern of DPBFZ zoning. In addition, the antibody-antigen affinity function, the clone mechanism, and mutation strategy were constructed and improved to solve the DPBFZ problem with a spatial optimization feature. Finally, Tongxu County in Henan province was selected as the study area, and a controlled experiment was set up according to different target preferences. The results show that the model proposed in this paper is operational in the work of delineating DPBFZ. It not only avoids the adverse effects of subjective factors in the delineation process but also provides multiple scenarios DPBFZ layouts for decision makers by adjusting the weighting of the objective function.
Keywords
delineation of DPBFZ; Immune clonal selection algorithm; Spatial optimization; Multi-objective decision; Ecological protection;
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