CLUE-S模型应用进展与改进研究

Recent Progresses on the Application and Improvement of the CLUE-S Model

土地利用变化是景观生态学重要的研究领域,通过模型模拟土地利用变化趋势是该领域的主要研究内容之一。CLUE-S模型可以全面考虑自然和人文因子,通过迭代方法综合空间分析和非空间分析,较好地模拟小尺度范围内土地利用变化情景,具有综合性、开放性、空间性、竞争效率性等特点,已经在国内外多个地区的土地利用变化研究中得到广泛应用,形成了较为成熟的研究方法。本文概括了CLUE-S模型在LUCC、环境效应和政策效应3方面的应用,从驱动因子选择、土地需求计算探讨了CLUE-S模型的改进和修正,总结出CLUE-S模型当前发展方向是提高预测精度和扩展模型应用,并指出与其他模型的耦合、模型的均衡假设和土地利用变化的过程效应是CLUE-S模型的下一步研究方向。

Land use change is one of the main research subjects of global environmental change and sustainable development.Land use models are useful for disentangling the complex suite of socio-economic and biophysical forces that influence the rate and spatial pattern of land use change and for estimating the impacts of changes on land use.Furthermore,models can support the exploration of future land use change under different scenarios and conditions.The CLUE-S（Conversion of Land Use and its Effects at Small Region Extent） model,which is based on comprehensive consideration on the basis of natural and human factors,can simulate small-scaled land use change scenarios with characteristics of integrity,openness,spatiality and competitive efficiency.This paper introduce the CLUE-S model improvements in the fields of the selection of driving factors,land requirements calculation,accuracy of the model calculation and model application development.Setting up the relationship between driving forces and spatial distribution is the core of CLUE-S model.Some suggestions for improving CLUE-S have also been put forward.Finally,we an draw three conclusions.First,CLUE-S is a mature integrated model for simulating the land use change.Using the spatial and non-spatial analysis,this model has been well developed and widely used in several areas in different land use fields all over the world.Second,coupled with other economic,statistic and mathematic models,the CLUE-S model has significant advantages in evaluating the land use change effects.Third,in the future,the improved prediction accuracy and the expansion of model application will probably better serve the objective of the understanding of land use change processes.