Scenarios analysis of land use change based on CLUE model in Jiangxi Province by 2030
基于CLUE模型的2030年江西省土地利用变化情景分析

Using CLUE(The Conversion of Land Use and its Effects)model based on GIS spatial analysis and statistics,this paper introduced three scenarios("Business as Usual Scenario","Planned Scenario"and"Optimal Scenario")to simulate the land use spatial change in Jiangxi Province from 2001 to 2030.The paper has developed three scenarios on land use change to conduct a comparative analysis.Scenarios provide an effective tool to assess the risks of current land use patterns and the policy options,and offer more comprehensive and meaningful scientific information to policy-makers from different approaches by taking various factors into account.As a result,scenario analysis plays a critical role in this study,where nine types of land use are identified to show what might take place under different scenarios.This model is applied to simulate the future land use scenarios in the next three decades,and to validate the simulated results with the land use map in 2005.The validation suggests that the model has accurately positioned the simulated results to an appropriate spatial location.The results are shown as follows.(1)"Business as Usual Scenario".The arable lands continue to decline,and lands for construction purposes increase sharply,while forested land areas remain stable.(2)"Planned Scenario".The arable lands continue to grow,and lands for construction purposes increase slightly and remain unchanged in 2020;forested land areas show a slight change,and high-density forest areas grow;the areas of rivers and lakes decrease marginally;while the areas of marshes and peat lands grow rapidly.(3) "Optimal Scenario".The forest areas grow relatively slowly than that under"Planned Scenario";while all the areas of rivers and lakes,marshes and peat lands increase significantly.The study also suggests that the CLUE model is very powerful in predicting the future land use change,and the land use changes under different scenarios vary greatly in spatial distribution.The results are expected to provide reference for future development and revision of land use planning,as well as for sustainable land management in the study area.