Detection of Bio-Meteorological Year-to-Year Variation by Using Digital Canopy Surface Images of a Deciduous Broad-Leaved Forest

Abstract

Clarification of the year-to-year variations and long-term trends of the timings of the start of leaf-expansion (SLE) and end of leaf-fall (ELF) is an important and challenging task because these timings affect spatial and temporal variations in water, heat and carbon cycles. Here, (1) we examined the relationships between daily mean air temperatures and the timings of SLE and ELF by using digital camera images in a cool-temperate deciduous broad-leaved forest in Japan from 2004 to 2011, and constructed a simple statistical phenology model based on their relationships, and (2) we then evaluated year-to-year variations and long-term trends in the timings of SLE and ELF over the past 51 years (1961−2011) by using that phenology model. We found that (1) the year-to-year variations in daily mean air temperatures over 2°C and below 18°C well affected those in the timings of SLE and ELF, respectively, and (2) a significant long-term linear trend in the timing of ELF (it moved later; 2.7 days decade −1) and the length of the leafy period were observed (it prolonged; 3.4 days decade −1 ), but no long-term trend was evident in the timing of SLE.

Utilization of ground-based digital photography for the evaluation of seasonal changes in the aboveground green biomass and foliage phenology in a grassland ecosystem

“…Use of the threshold value of the camera-based vegetation index is one of the useful approaches for automatic detection of the phenological events such as leaf-flush (Nagai et al, 2013). Inoue et al (2014) statistically evaluated the suitable threshold value of GEI for detection of the timings of start of leaf-flush and end of leaf-fall in a deciduous broad-leaved forest in Japan by using daily canopy surface photographs over 10 years.…”

Phenology of leaf morphological, photosynthetic, and nitrogen use characteristics of canopy trees in a cool‐temperate deciduous broadleaf forest at Takayama, central Japan

“…Another contribution of ecophysiological research on forest leaf phenology is to improve the ecophysiological uses of remote sensing data (Muraoka and Koizumi 2009). Recently, researchers have attempted to observe the seasonal changes in the ecophysiological status of a forest canopy using indirect methods such as in situ and satellite remote sensing (Nishida 2007;Muraoka et al 2013) and digital camera images (Richardson et al 2007;Ahrends et al 2009;Nagai et al 2013). The spectral reflectance of the canopies measured by spectroradiometers and RGB signals recorded by a digital camera can reflect the leaf anatomical, biochemical, and photosynthetic properties of the forest canopy.…”

“…In addition to short-term changes, the seasonal changes (i.e., phenology) in leaf/canopy morphology and physiology reflect the responses to environmental changes (e.g., Wilson et al 2001;Ito et al 2006;Muraoka et al 2010). Recent in situ remote sensing observations of temperate forests have emphasized the functional importance of phenology in determining canopy photosynthesis (e.g., Richardson et al 2006;Nakaji et al 2007;Saitoh et al 2012;Nagai et al 2013). However, it is important to increase our understanding of leaf-level phenology with respect to photosynthesis and related components such as chlorophylls and nitrogen, because photosynthesis is the fundamental process controlling tree growth and the responses of the forest carbon cycle to environmental change.…”

Year-to-year blooming phenology observation using time-lapse digital camera images

“…(3) Finally, we calculated the green excess index (GEI; Richardson et al, 2007) and the HUE values in the hue, saturation, and value (hexagonal cone color model; Smith, 1978;Takagi and Shimoda, 2004), which have been examined in many previous studies (Richardson et al, 2007;Ide and Oguma, 2010;Mizunuma et al, 2011;Saitoh et al, 2012;Morris et al, 2013;Nagai et al, 2013;Nijland et al, 2013):…”

“…To solve these problems, we (Nagai et al, 2013) have suggested a biometeorological observation method that uses a time-lapse digital camera and an automatic weather station (AWS), and we have used the method to examine the relationship between yearto-year variations in leaf expansion and defoliation and daily air temperature in a cool-temperate deciduous broad-leaved forest in Japan (Nagai et al, 2013). Time-lapse digital cameras have been installed not only at ecological study sites (Richardson et al, 2007;Ahrends et al, 2009;Nagai et al, 2013) but also in public areas, such as national parks, tourist sites, and along highways (Graham et al, 2010;Ide and Oguma, 2010;Morris et al, 2013). The success of these studies suggests that spatiotemporal variability in blooming phenology can be detected over wide areas using timelapse digital camera images at multiple points.…”