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Library equilibrium analysis of the land use structure in the Yunnan Province, China

equilibrium analysis of the land use structure in the Yunnan Province, China

equilibrium analysis of the land use structure in the Yunnan Province, China

Resource information

Date of publication
декабря 2014
Resource Language
ISBN / Resource ID
AGRIS:US201400152659
Pages
393-404

Global land use structure is changing rapidly due to unceasing population growth and accelerated urbanization, which leads to fierce competition between the rigid demand for built-up area and the protection of cultivated land, forest, and grassland. It has been a great challenge to realize the sustainable development of land resources. Based on a computable general equilibrium model of land use change with a social accounting matrix dataset, this study implemented an equilibrium analysis of the land use structure in the Yunnan Province during the period of 2008–2020 under three scenarios, the baseline scenario, low TFP (total factor productivity) scenario, and high TFP scenario. The results indicated that under all three scenarios, area of cultivated land declined significantly along with a remarkable expansion of built-up area, while areas of forest, grassland, and unused land increased slightly. The growth rate of TFP had first negative and then positive effects on the expansion of built-up area and decline of cultivated land as it increased. Moreover, the simulated changes of both cultivated land and built-up area were the biggest under the low TFP scenario, and far exceeded the limit in the Overall Plan for Land Utilization in the Yunnan Province in 2020. The scenario-based simulation results are of important reference value for policy-makers in making land use decisions, balancing the fierce competition between the protection of cultivated land and the increasing demand for built-up area, and guaranteeing food security, ecological security, and the sustainable development of land resources.

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Authors and Publishers

Author(s), editor(s), contributor(s)

Luo, Jiao
Zhan, Jinyan
Lin, Yingzhi
Zhao, Chunhong

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Geographical focus