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Simulation on optimized allocation of land resource based on DE-CA model

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  • Wang, Shi-dong
  • Wang, Xin-chuang
  • Zhang, He-bing

Abstract

Optimization of land resource allocation is a research hot spot in land science. In this study, a new differential evolution-cellular automata (DE-CA) model was established. With this model, the quantitative structure of land-use was optimized with differential evolution algorithm (DEA). The results obtained were then used as the quantitative restraint condition of CA model to optimize the land-use spatial patterns. The application of this model successfully achieved the proper combination of land-use quantitative structure with the land-use spatial pattern, which overcame the problem in previous studies with particular emphasis on either optimization of land-use quantitative structure or optimization of spatial patterns in the field of optimization of land resource allocation. Finally, we applied the established DE-CA model to optimize the allocation of land resources for the year 2010 and 2020 based on 2005 and 2010, respectively, in Dawa County and Liaoning Province in northeast of China. The accuracy and reasonability of the optimized results were analyzed and assessed. The results showed that the overall accuracy of the optimized results was 84.56% with Kappa coefficient of 0.7860, indicating the good performance of the established DE-CA model. Furthermore, the simulated scheme was shown to be consistent with the real situation. Thus, this model can provide the references for formulation of the regional land-use planning and provide scientific basis for the substantial utilization of land.

Suggested Citation

  • Wang, Shi-dong & Wang, Xin-chuang & Zhang, He-bing, 2015. "Simulation on optimized allocation of land resource based on DE-CA model," Ecological Modelling, Elsevier, vol. 314(C), pages 135-144.
    • Handle: RePEc:eee:ecomod:v:314:y:2015:i:c:p:135-144
    DOI: 10.1016/j.ecolmodel.2015.07.011
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    References listed on IDEAS

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    1. Francisco, Sergio R. & Ali, Mubarik, 2006. "Resource allocation tradeoffs in Manila's peri-urban vegetable production systems: An application of multiple objective programming," Agricultural Systems, Elsevier, vol. 87(2), pages 147-168, February.
    2. Chuan Lin & Anyong Qing & Quanyuan Feng, 2011. "A new differential mutation base generator for differential evolution," Journal of Global Optimization, Springer, vol. 49(1), pages 69-90, January.
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    Cited by:

    1. Lingling Chen & Brijesh Thapa & Jinwon Kim & Lin Yi, 2017. "Landscape Optimization in a Highly Urbanized Tourism Destination: An Integrated Approach in Nanjing, China," Sustainability, MDPI, vol. 9(12), pages 1-20, December.
    2. Dinghua Ou & Xingzhu Yao & Jianguo Xia & Xuesong Gao & Changquan Wang & Wanlu Chen & Qiquan Li & Zongda Hu & Juan Yang, 2019. "Development of a Composite Model for Simulating Landscape Pattern Optimization Allocation: A Case Study in the Longquanyi District of Chengdu City, Sichuan Province, China," Sustainability, MDPI, vol. 11(9), pages 1-35, May.
    3. Juan Wang & Jiaqi Lv & Wenping Zhang & Tianqian Chen & Yang Yang & Jinjin Wu, 2022. "Land-Use Pattern Evaluation Using GeoSOS-FLUS in National Territory Spatial Planning: A Case Study of Changzhi City, Shanxi Province," Sustainability, MDPI, vol. 14(21), pages 1-18, October.

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