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Suitability assessment of urban land use in Dalian, China using PNN and GIS

Author

Listed:
  • Ziqian Kang

    (Jilin University
    Nankai University)

  • Shuo Wang

    (Jilin University
    Jilin University)

  • Ling Xu

    (Dalian University of Technology)

  • Fenglin Yang

    (Dalian University of Technology)

  • Shushen Zhang

    (Dalian University of Technology)

Abstract

The suitability assessment of land use is crucial to avoid wasting land resources. However, the traditional methods with subjective weights are prone to reduce the reasonability and reliability of assessment. For filling this knowledge gap, the probability neural network (PNN) coupled with GIS was adopted to evaluate the land use suitability in this paper. According to the applications of the urban land resource, the land use was divided into three types (resident, industry and ecological reserve). Thus, the three different assessment criteria systems were built for the three land use types. The result of residential land use indicated that the most suitable, suitable and normal suitable residential land were 401, 272 and 12,406 km2 and mainly located in Changhai, Lvshun and Pulandian accordingly. The most suitable land for industry was in Ganjingzi, Jinzhou and Wafangdian and accounted for 22% of the total area. While the most suitable land for ecological reserve was in Pulandian and Zhuanghe with the area of 1967 km2. The results indicated that the south of Dalian was suitable for the residential land use, north of Dalian was suitable for the ecological land use and the central was suitable for industrial land use. The results were coincided to the actual spatial distribution of land use. The proposed PNN coupled with GIS assessment method in suitability of land use is conducted to provide a more reasonable assessment result that can be used by managers and regulators.

Suggested Citation

  • Ziqian Kang & Shuo Wang & Ling Xu & Fenglin Yang & Shushen Zhang, 2021. "Suitability assessment of urban land use in Dalian, China using PNN and GIS," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(1), pages 913-936, March.
    • Handle: RePEc:spr:nathaz:v:106:y:2021:i:1:d:10.1007_s11069-020-04500-z
    DOI: 10.1007/s11069-020-04500-z
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    References listed on IDEAS

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    1. Al-Yahyai, Sultan & Charabi, Yassine & Gastli, Adel & Al-Badi, Abdullah, 2012. "Wind farm land suitability indexing using multi-criteria analysis," Renewable Energy, Elsevier, vol. 44(C), pages 80-87.
    2. Ehsan Noorollahi & Dawud Fadai & Mohsen Akbarpour Shirazi & Seyed Hassan Ghodsipour, 2016. "Land Suitability Analysis for Solar Farms Exploitation Using GIS and Fuzzy Analytic Hierarchy Process (FAHP)—A Case Study of Iran," Energies, MDPI, vol. 9(8), pages 1-24, August.
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    Cited by:

    1. Xiangnan Fan & Yuning Cheng & Yicheng Li, 2023. "Multi-Scenario Land Use Simulation and Land Use Conflict Assessment Based on the CLUMondo Model: A Case Study of Liyang, China," Land, MDPI, vol. 12(4), pages 1-26, April.
    2. Keyu Luo & Zhenyu Wang & Wei Sha & Jiansheng Wu & Hongliang Wang & Qingliang Zhu, 2021. "Integrating Sponge City Concept and Neural Network into Land Suitability Assessment: Evidence from a Satellite Town of Shenzhen Metropolitan Area," Land, MDPI, vol. 10(8), pages 1-16, August.
    3. Yanru Zhao & Xiaomin Zhao & Xinyi Huang & Jiaxin Guo & Guohui Chen, 2022. "Identifying a Period of Spatial Land Use Conflicts and Their Driving Forces in the Pearl River Delta," Sustainability, MDPI, vol. 15(1), pages 1-17, December.

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    Keywords

    Suitability; Land use; PNN; GIS; Dalian;
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