Color characteristics of Beijing's regional woody vegetation based on Natural Color System

Abstract

Seasonality is a typical characteristic of Beijing's regional vegetation, and plant color is one of the most prominent visual factors of vegetation dynamic. In this research, we explored the composition and dynamic characteristics of plant color in Beijing's urban vegetation, involving the analysis of overall characteristics and respective features of leaf, flower, and fruit colors. Color data was collected from 177 woody plant species in Beijing Botanical Garden, spanning their annual life cycle, and identified with the colorimetry of the Natural Color System (NCS). Correlation and regression analyses were applied to reveal the temporal dynamic features of overall plant color richness. Cluster analysis was applied to categorize tree species based on typical colors of various plant organs. Color richness and color dispersion were introduced as two factors to measure color diversity of various tree species, applied in species evaluation by sorting and principal component analysis (PCA). Color dispersion of three‐dimensional NCS data was measured with a modified SD based on the calculation of mean spatial distance in the NCS space. Main results are as follows. The first part is plant color composition. The composition of all plant colors contains 862 NCS color species, 20 blackness species ranging from 3 to 90, 20 chromaticness species ranging from 0 to 90, 35 hue species ranging from G10Y‐B90G, and N. The second part is temporal dynamic of overall color richness. Leaf color richness and total color richness are significantly positively correlated with pentad (5‐day) sequence; flower color richness is significantly negatively correlated with pentad sequence; and fruit color richness first increases and then decreases over time. The third part is cluster analysis of tree species. Based on typical growing‐leaf color, various tree species were clustered into 6 categories; based on typical senescent‐leaf color, various tree species were clustered into 6 categories; based on typical flower color, various tree species were clustered into 15 categories; based on typical fruit color, various tree species were clustered into 7 categories. The fourth part is color diversity evaluation of various tree species with PCA. According to the PCA of flower‐leaf color diversity, the species with higher leaf color diversity and higher flower color diversity include Cotinus coggygria, Lagerstroemia indica, and Amygdalus triloba; the species with higher flower color diversity and lower leaf color diversity include Campsis radicans and Tamarix chinensis; the species with higher leaf color diversity and lower flower color diversity include Acer ginnala and Crataegus pinnatifida; the species with lower color diversity both for flower and leaf colors include Fontanesia fortune and Gleditsia sinensis. According to the PCA of leaf color diversity, the species with higher leaf color diversity in both leaf growth period and leaf senescence period include Diospyros kaki, Lagerstroemia indica and Paeonia suffruticosa; the species with hi...

Quantitative study on landscape colors of plant communities in urban parks based on natural color system and M‐S theory in Nanjing, China

“…Blackness is converted to lightness (lightness = 100% − blackness); chroma are variables that can be read directly from the color number between 0% and 100% (0, 10% … 100%), which can be used in SPSS statistics and other calculations without conversion, whereas the hue value needs to be converted into quantitative data, and the conversion process is shown in Table 3 . 2 Also taking S5040‐R60B as an example, after conversion, its color number coding will be transformed into three‐dimensional data (50%, 40%, 4/5π). According to the brightness value, the saturation value and hue value obtained from color collection and transformation, the order factor, complexity factor, and aesthetic degree (color harmony degree) of 12 plant community landscape colors are calculated one by one by using the aesthetic degree formula “ M .” Collect the color of the external environment of the plant community, use the color mixer, which is a color analysis software, to mix the typical landscape color of the plant community with the color of the external environment, and calculate the color suitability with the M‐S theory.…”

“…Blackness is converted to lightness (lightness = 100% − blackness); chroma are variables that can be read directly from the color number between 0% and 100% (0, 10% … 100%), which can be used in SPSS statistics and other calculations without conversion, whereas the hue value needs to be converted into quantitative data, and the conversion process is shown in Table 3 . 2 …”

“…As the first element of visual perception, the color beauty and harmony of the plant landscape directly affect the quality of the landscape 1 . The color of the plant landscape is an important factor affecting the quality of the urban landscape 2,3 . Therefore, on the basis of investigating the color of the plant community landscape, further quantifying the color harmony degree of the plant community is an important means of plant landscape color design.…”

“…One is the colorimetric method. At present, the commonly used colorimetric cards include Royal horticultural society (RHS) color card, 10 natural color system (NCS) color card, 2 and Munsell color card, 11 which are suitable for collecting a large number of color data. The second is the instrument measurement method, which is mainly completed by a colorimeter.…”

Genetic diversity and conservation of Siberian apricot (Prunus sibirica L.) based on microsatellite markers

“…Siberian apricot ( Prunus sibirica L.) is a deciduous perennial woody tree species of the genus Prunus in the Rosaceae subfamily Prunoideae 1 . Given its white or pinkish flowers in spring, ripe yellow fruit in summer, and highly diverse leaf colors in autumn, the tree is considered to have particular ornamental value 2 , 3 . As a pioneer tree species in the restoration of vegetation, P. sibirica can tolerate cold, drought, and barren land and, thus, has high ecological value 1 , 4 .…”