Using digital camera images to detect canopy condition of deciduous broad-leaved trees

Background: Recent studies have described a technique that incorporates a digital camera to observe aspects of tree phenology, such as leaf expansion and leaf fall. This technique has shown that seasonal patterns of red, green and blue digital numbers (RGB_DN) extracted from digital images differ between species. Aims: To identify the different characteristics of phenology between species by examining RGB_DN, the relationship between the seasonal patterns of RGB_DN and ecological characteristics for various species were evaluated throughout the year. Methods: The relationship between the normalised RGB_DN values extracted from digital images and in situ leaf area index (LAI) and leaf chlorophyll content (indicated by soil and plant analyser development, SPAD) was examined for three dominant species for multiple years in a cool-temperate, deciduous, broad-leaved forest in Japan. Results: The RGB_DN values in spring were not useful in detecting the different characteristics of leaf-flush patterns between species. In contrast, RGB_DN values in autumn showed differences in leaf-colouring as well as in leaf-fall patterns and timings between species. Conclusion: Differences in autumn phenology between tree species can be detected by using the normalised RGB_DN technique, while the technique cannot be applied in spring.