Scenario-based simulation of land use in Yingtan (Jiangxi Province, China) using an integrated genetic algorithm-cellular automata-Markov model

Ye, Ying-cong; Kuang, Li-hua; Zhao, Xiao-min; Guo, Xi

Scenario-based simulation of land use in Yingtan (Jiangxi Province, China) using an integrated genetic algorithm-cellular automata-Markov model

2020

Ye, Ying-cong | Kuang, Li-hua | Zhao, Xiao-min | Guo, Xi

Yingtan is a rapidly urbanizing city in Jiangxi Province, South China. During rapid urbanization, construction land is expanded at the expense of cropland and forest. Although economic benefits are gained, ecological and environmental damage is irreversible. In this study, a methodological framework for land use simulation using an integrated genetic algorithm-cellular automata-Markov model is proposed to assess the relationship between economic development and cropland protection in Yingtan. This framework considers both the economic and ecological benefits of different land use types. Three land use scenarios are evaluated to seek recommendations for land use practice. The results show that the areas with high suitability for cropland and construction are mainly concentrated in urban fringes. Under the green development scenario, the area of new construction land can meet the land demand for population growth and economic development proposed for 2025 based on population forecasting and government interviews. The expansion for construction land is decreased by ~ 35 km² while the cropland area is increased by ~ 20 km² compared with those under natural and controlled development scenarios. Additionally, ecological losses are lowest under the green development scenario. In conclusion, the green development scenario is conducive to both cropland and ecological protection, which is of relevance for future spatial planning in Yingtan.

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