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    近自然森林景观空间结构参数化设计研究

    Parametric design of close-to-nature forest landscape spatial structure

    • 摘要:
        目的  现有近自然森林景观营造手段缺乏在设计阶段对群落空间结构的控制,制约了城市森林的营造效益。可以利用邻体相互作用的群落空间结构生成机制建立设计算法,实现近自然森林空间结构的参数化设计。
        方法  基于树冠竞争指数构建设计竞争指数(DCI)作为近自然森林空间结构的优化规则,利用该规则开发包含植株生境适宜性预分布、空间结构迭代优化两个模块的设计算法。并参照北京市浅山地区天然森林群落特征,采用该算法对北京市青龙湖公园内的一处场地进行应用,验证其可行性。
        结果  在应用情景中,该算法能够通过优化规则降低植株间的DCI,实现空间结构的优化,并根据预设的树种类型、适宜性和比例生成符合近自然森林景观特征的植株分布平面图。
        结论  该算法能够生成符合近自然森林群落空间结构特征的设计群落,可以作为一种近自然森林景观空间结构生成的辅助设计方法,但需要根据近自然指标进一步优化算法,积累近自然森林植物种类、形态特征和适宜性的特征参数,完善该算法对近自然森林群落的仿真程度。

       

      Abstract:
        Objective  Existing methods for creating close-to-nature forest landscapes lack control over the spatial structure of communities at the design stage restricted the benefits of urban forest construction. We can use the community spatial structure generation mechanism based on neighbor interactions to establish a design algorithm, realizing parametric design of near-natural forest spatial structure.
        Method  We built a design competition index (DCI) based on the crown competition index as an optimization rule for the spatial structure of close-to-nature forest. We used this rule to develop a design algorithm that included two modules: pre-distribution of plant habitat suitability, and iterative optimization of spatial structure. We applied this algorithm to a site in the Qinglong Lake Park in Beijing, referencing the characteristics of natural forest communities in the hilly areas of Beijing to verify its feasibility.
        Result  In the application scenario, this algorithm can reduce the DCI among plants through the optimization rule, optimize the spatial structure, and generate a plant distribution plan conforming to the characteristics of close-to-nature forest landscapes according to preset tree species types, suitability and proportion.
        Conclusion  This algorithm can generate a design community conforming to the spatial structure characteristics of close-to-nature forest communities. It can serve as an auxiliary design method for generating the spatial structure of close-to-nature forest landscapes. However, it needs to be further optimized according to close-to-nature forest indicators, accumulate feature parameters of close-to-nature forest plant species, morphological features and suitability, and improve the simulation degree of this algorithm for close-to-nature forest communities.

       

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