Predicting tree preferences from visible tree characteristics
Predicting tree preferences from visible tree characteristics
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DOI：
10.1007/s10342-017-1042-7
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发表时间：
2017-06-01
影响因子：
2.8
通讯作者：
Gillner, Sten
中科院分区：
文献类型：
--
作者：
Hofmann, Mathias;Gerstenberg, Tina;Gillner, Sten
本文从心理学的角度对城市住区树木的选择进行了探讨。非专业参与者根据偏好对60种适合城市种植地点的树种进行了评级。然后，我们使用向外树特征来预测偏好评级。在树木偏好的回归模型中，25种不同的植物特征可作为可能的预测因子。我们发现针叶树和落叶树之间的差异、最大树高和冠高宽比是有价值的偏好预测因子，解释了70%以上的方差。这为景观偏好的进化理论增加了支持。本文所建立的回归模型可用于利用其他树种的已知物理数据计算其偏好估计，从而为绿地规划中的树种选择工作提供便利。通过指定与偏好相关的树木特征，我们的研究结果还可以为以整体外观为规划目标的地点选择不同物种的过程提供信息。
This paper presents a psychological perspective to the selection of trees for urban residential areas. Sixty tree species suitable for urban planting sites were rated by lay participants regarding preference. We then used outward tree features to predict the preference ratings. Twenty-five different plant characteristics served as possible predictors in a regression model for tree preference. We found that the distinction between conifers and deciduous trees, the maximum tree height, and the crown height-to-width ratio were valuable predictors for preference, explaining more than 70% of the variance. This adds support for evolutionary theories of landscape preference. The regression model presented in this paper can be applied to calculate a preference estimate for other tree species using their known physical data, which may facilitate tree selection tasks in green space planning. By specifying preference-relevant tree characteristics, our findings may also inform the process of selecting diverse species for sites where a homogenous overall appearance is a planning goal.