HUBEI AGRICULTURAL SCIENCES ›› 2022, Vol. 61 ›› Issue (4): 36-42.doi: 10.14088/j.cnki.issn0439-8114.2022.04.006

• Resource & Environment • Previous Articles     Next Articles

Multi-objective collaborative optimization of territorial space based on the constraints of resource carrying capacity: A case study of Jinzhong city

GUO Dong-xiao, ZHU Hong-fen, LIU Hui-fang, BI Ru-tian   

  1. College of Resource and Environment, Shanxi Agricultural University, Jinzhong 030801,Shanxi,China
  • Received:2021-09-24 Online:2022-02-25 Published:2022-03-18

Abstract: Based on the assessment of resources and environment carrying capacity, the weak points was identified, the maximum carrying capacity scale was determined, and the distribution of territorial space was optimized. Taking Jinzhong city as the study area, the carrying capacity under the constraints of short boards was calculated based on the analysis of resource carrying capacity in the study area. The quantitative structure of land use types and the spatial distribution of optimal scenario under the four scenarios of ecological protection, food security, economic growth and balanced development were obtained by coupling multi-objective genetic algorithm and FLUS model. The results showed that the background resource and carrying capacities of current environmental and resource for all types of space were restricted by water resource, and the shortage of water resource was the bottleneck that would affect the sustainable development of Jinzhong city in the future; The carrying area of urban construction was 343.35 km2, rural construction was 746.17 km2, and arable land was 3 683.50 km2 under the restriction of water resource; The area of construction was overloaded in different extent. The optimized schemes under the four scenarios were obtained based on the multi-objective genetic algorithm; The scenario of balanced development was the best among the four scenarios, and the national spatial structure were more reasonable; Its ecological benefit was 25.243 billion, the economic benefit was 1 365.017 billion, the comprehensive benefit was better than the other three scenarios.

Key words: resource and environmental carrying capacity, optimization of territorial space, multi-objective genetic algorithm, FLUS model

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