Modeling the scenic beauty of autumnal tree color at the landscape scale: A case study of Purple Mountain, Nanjing, China

《Modeling the scenic beauty of autumnal tree color at the landscape scale: A case study of Purple Mountain, Nanjing, China》

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关键字: Autumnal tree color;Distribution pattern;Landscape scale;Modeling;Purple Mountain;Scenic beauty evaluation

作者单位: College of Forestry, Nanjing Forestry University, No. 159 Longpan Road, Nanjing, Jiangsu, China;Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing, China;College of Forestry, Nanjing Forestry University, No. 159 Longpan Road, Nanjing, Jiangsu, China;Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing, China

摘要: Scenic forests are a basic component of forest parks. Evaluating the beauty of the color of scenic forests is an important consideration in scientific management measures. The Purple Mountain National Forest Park in Nanjing was considered the case study area. Using the autumn scenic forest typical sample survey in 2017 and color beauty questionnaire surveys of tourists as the main information sources, the beauty of the autumn color in the study area was quantitatively analyzed by using multiple linear regression and random forest models. The results reveal the following: (1) of the two evaluation models, the fitting accuracy of the random forest model is higher than that of the multiple linear regression model with a correlation coefficient of 0.91; (2) the main affecting factors include the canopy density (CD), average diameter at breast height (DBH), average tree height (H), plot volume (PV), quantification of orange (O), number of seasonal changing colors (SC), average hue value (AH), number of color categories (CC), distance to residence (DRE), distance to road (DRO), slope (SL) and aspect (AS); and (3) the distribution of the color scenic beauty value gradually decreased from the southwest to northeast. The results of this study show that the color scenic beauty of an urban forest park in autumn can be evaluated using a quantitative model.