大数据分析下园林景观空间格局梯度优化仿真

Gradient Optimization Simulation of Landscape Spatial Pattern under Big Data Analysis

为了优化园林景观空间的梯度格局,需要对园林景观空间格局梯度优化方法进行研究。当前园林景观空间格局梯度优化方法得到的梯度格局中植物种类少,且分布不均匀,不能有效的对园林景观空间格局的梯度进行优化。在大数据分析的基础上提出一种园林景观空间格局梯度优化方法,通过园林景观格局指数对园林景观的梯度格局进行分析。根据分析结果计算园林景观空间格局梯度的生态环境贡献值,并采用单因子评价方法得到影响因子的评价指数,根据评价指数计算园林景观空间格局梯度的综合测力。通过指数方法得到梯度格局的景观流,结合生态环境贡献值和综合测力,对园林景观空间格局梯度进行优化。仿真结果表明,所提方法优化的梯度格局中植物种类多,分布均匀,可以有效的对园林景观空间格局梯度进行优化。

This paper proposes a gradient optimization method for garden landscape spatial pattern based on big data analysis.At first,the gradient pattern of garden landscape was analyzed through the garden landscape pattern index.According to the analysis result,the ecological environment contribution value of spatial pattern gradient of garden landscape was calculated and the single-factor evaluation method was used to get evaluation index impacting factor.Then comprehensive dynamometry of spatial 'pattern gradient of garden landscape was calculated based on the evaluation index.Moreover,the exponential method was used to obtain the landscape flow of gradient pattern.Finally,combined ecological environment contribution value with comprehensive dynamometry,the spatial gradient pattern of garden landscape was optimized.Simulation results prove that there are many plant species in the gradient pattern optimized by proposed method,which can effectively optimize the gradient of garden landscape spatial pattern.