Literature DB >> 32462617

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

Ying-Cong Ye1, Li-Hua Kuang1, Xiao-Min Zhao2, Xi Guo1.   

Abstract

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.

Keywords:  Cellular automata; Genetic algorithm; Land use scenario; Markov; Urban expansion

Year:  2020        PMID: 32462617     DOI: 10.1007/s11356-020-09301-2

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  1 in total

1.  An Integrated Spatial Autoregressive Model for Analyzing and Simulating Urban Spatial Growth in a Garden City, China.

Authors:  Bingkui Qiu; Min Zhou; Yang Qiu; Shuhan Liu; Guoliang Ou; Chaonan Ma; Jiating Tu; Siqi Li
Journal:  Int J Environ Res Public Health       Date:  2022-09-17       Impact factor: 4.614

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.