Abstract
The increased focus on land resources is a result of global climate change. For human life and progress, land resources provide a key foundation. Using land resources under sensible regulations can enable sustainable development in order to better adapt to climate change. In this study, we used the Malmquist index to compute the outcomes and spatial distribution of land use efficiency in Shanxi Province during 2006–2019. According to the findings, ecologically vulnerable areas have less efficient land use than areas with rapid economic growth. Therefore, to more effectively resolve the tensions between economic development and ecological conservation and to provide scientific guidance to decision makers, we need to model future land use in Shanxi Province driven by socio-economic systems. To predict future land use demand and its spatial distribution under the influence of socio-economic and government policies, this study combines the Computable General Equilibrium of Land Use Change (CGELUC) model and Dynamics of Land System (DLS) model. Under the green development scenario, the reduction rates of forest land and grassland are 2.09 % and 1.65 %, respectively, which is the slowest reduction of ecological land among the three scenarios. Development of ecological land such as forests and grasslands are severely prohibited by government regulations. The lowest carbon sequestration reduction rate of 1.62 % is registered in Shanxi Province under the green development scenario. Construction land increases more quickly under the economic priority development scenario, with a growth rate of 33.02 %. Ecological land, including grasslands and forests, is declining. Under the scenario of economic development priority, the ecological land in Shanxi Province will inevitably be sacrificed. Therefore, the government should strive to actively overcome barriers to the development of land resources for ecological protection as this is a key region for that purpose.
Original language | English |
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Article number | 106810 |
Journal | Land Use Policy |
Volume | 132 |
Publication status | Published - Sept 2023 |
Keywords
- Land resources
- Scenario simulation
- CGELUC- DLS model
- SAM table
- Land use policy