Abstract
The relationship between scenic beauty grade and measured tree indicators was studied through evaluation of 427 photos of individual Pinus tabulaeformis trees by using the scenic beauty estimation (SBE) method. Thirteen indices to reflect trunk, crown and stem-to-canopy ratios of individual trees were evaluated by invited students. Results showed that students preferred large diameters at breast height, full canopies and straight stems or some trees with minor crook stems. Tree height had a minor contribution to individual tree quality. Correlation analysis and factor analysis were employed to select indices and to integrate them into a comprehensive index. The stepwise method of nonlinear model incorporation of four comprehensive indices—tree crown form, stem-crown coordination, tree growth and stem for—were proven valuable in order to evaluate the scenic beauty of individual trees.
Highlights
Modern urbanization requires forests to serve more functions than just timber production and ecological conservation
Analysis of variance indicated that most relationships between indices and Scenic beauty estimation (SBE) grades were significant or very significant at the 0.05 level, except for indices including crown symmetry degree (CSD), crown width/diameter ratio (RDCW) and stem lean degree (SLD) (Table 4)
The multiple comparisons suggest that most indices changed linearly with SBE grade, but annual average increment of tree height (AIH), diameter/tree height ratio (RDH)
Summary
Modern urbanization requires forests to serve more functions than just timber production and ecological conservation. The core objective of urban forest management has been upgraded to include the creation of a more beautiful forest landscape for attracting outdoor recreation activities [1]. In order to achieve the scientific management of scenic forests, their beauty should be evaluated properly and precisely [2]. Scenic forests are evaluated through several indices, which provide an assessment method to identify what types of forests are more attractive for most people. Thereafter, the multiple regression linear model was used to evaluate the forests according to the preferred scenic physical characteristics at the landscape scale [4], near-view-forest [5,6,7] and isolated tree scenery [8]. A nonlinear model was applied to the studies of Analytic Hierarchy Process (AHP) [1] and neural networks [7,10]
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