基于历史情景的FLUS模型邻域权重设置——以闽三角城市群2030年土地利用模拟为例
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摘要
以闽三角城市群2030年土地利用模拟为例,针对FULS模型邻域权重参数提出一种基于历史情景的设置方法。首先以2015年土地利用数据为基础,结合人工神经网络算法综合12个自然、社会、经济驱动因子计算各土地类型的出现概率和空间分布,然后依据对历史情景的分析,分别用马尔可夫链和分析景观格局指数的方法设定相关参数,最后用自适应惯性竞争元胞自动机模拟闽三角城市群2030年的土地利用情景。分析发现,同时间尺度各土地类型TA(Total Area)的变化量可以较好的反映其扩张强度,由强到弱依次为建设用地、水域及滩涂、其他土地、草地、林地及农田;TA变化量的无量纲值在数据意义和数据结构方面均较好地契合FLUS模型邻域权重的参数要求;结合各土地类型TA变化量和扩张强度间的相互关系来看,到2030年农田受建设用地扩张的影响最为严重,大量土地由农田、林地、草地及其他土地转变为建设用地或水域及滩涂;建设用地持续扩张,闽三角城市群空间一体化格局基本形成,其余各土地类型被进一步分离,同类型斑块更趋于独立发展。综合参数设置过程和模拟结果来看,TA变化量的无量纲值可为FLUS模型的邻域权重参数设置提供一种客观可行的方法。
In this study, a historical scene-based setting method is proposed for the parameter Weight of Neighborhood of the FLUS model by simulating the land use scenario of urban agglomeration of the Golden Triangle of Southern Fujian in 2030. Firstly, based on the land use data in 2015, the occurrence probability and spatial distribution of each land use type were calculated with the artificial neural network algorithm, which integrates 12 natural, social and economic driving factors. According to the analysis of historical scenarios, the parameters of the FLUS model were confirmed via the Markov Chain and the landscape pattern indexes analysis method. Finally the Self-Adaptive Inertia and Competition mechanism Cellular Automata were used to simulate the land use scenario of urban agglomeration of the Golden Triangle of Southern Fujian in 2030. According to the analysis, the variation of TA(Total Area) at the same time scale could better reflect each land use type′s expansion intensity and were ranked follows: construction land, water area and tidal flat, other land, grassland, woodland, and cultivated land. The dimensionless value of TA variation was in good agreement with the Weight of Neighborhood of the FLUS model in terms of data meaning and data structure. Combined the relationship between the TA variation and the expansion intensity of each land use type, the cultivated land would be most affected by the expansion of construction land until 2030. A large amount of land will be converted constantly from farmland, woodland, grassland and other land into construction land or water area and tidal flat. The construction land will continue to expand, the spatial integration pattern of the urban agglomeration of the Golden Triangle of Southern Fujian will basically form, other land use types will be further separated, and the patches of same land use types would progress independently. Taking the parameter setting process and simulation results into account, the dimensionless value of TA variation can provide an objective and feasible method for setting the Weight of Neighborhood parameters of FLUS model.
In this study, a historical scene-based setting method is proposed for the parameter Weight of Neighborhood of the FLUS model by simulating the land use scenario of urban agglomeration of the Golden Triangle of Southern Fujian in 2030. Firstly, based on the land use data in 2015, the occurrence probability and spatial distribution of each land use type were calculated with the artificial neural network algorithm, which integrates 12 natural, social and economic driving factors. According to the analysis of historical scenarios, the parameters of the FLUS model were confirmed via the Markov Chain and the landscape pattern indexes analysis method. Finally the Self-Adaptive Inertia and Competition mechanism Cellular Automata were used to simulate the land use scenario of urban agglomeration of the Golden Triangle of Southern Fujian in 2030. According to the analysis, the variation of TA(Total Area) at the same time scale could better reflect each land use type′s expansion intensity and were ranked follows: construction land, water area and tidal flat, other land, grassland, woodland, and cultivated land. The dimensionless value of TA variation was in good agreement with the Weight of Neighborhood of the FLUS model in terms of data meaning and data structure. Combined the relationship between the TA variation and the expansion intensity of each land use type, the cultivated land would be most affected by the expansion of construction land until 2030. A large amount of land will be converted constantly from farmland, woodland, grassland and other land into construction land or water area and tidal flat. The construction land will continue to expand, the spatial integration pattern of the urban agglomeration of the Golden Triangle of Southern Fujian will basically form, other land use types will be further separated, and the patches of same land use types would progress independently. Taking the parameter setting process and simulation results into account, the dimensionless value of TA variation can provide an objective and feasible method for setting the Weight of Neighborhood parameters of FLUS model.
引文
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