Assessing the use of camera-based indices for characterizing canopy phenology in relation to gross primary production in a deciduous broad-leaved and an evergreen coniferous forest in Japan

Abstract

Recent studies have reported that seasonal variation in camera-based indices that are calculated from the digital numbers of the red, green, and blue bands (RGB_DN) recorded by digital cameras agrees well with the seasonal change in gross primary production (GPP) observed by tower flux measurements. These findings suggest that it may be possible to use camera-based indices to estimate the temporal and spatial distributions of photosynthetic productivity from the relationship between RGB_DN and GPP. To examine this possibility, we need to investigate the characteristics of seasonal variation in three camera-based indices (green excess index [GE], green chromatic coordinate [rG], and HUE) and the robustness of the relationship between these indices and tower flux-based GPP and how it differs among ecosystems. Here, at a daily time step over multiple years in a deciduous broad-leaved and an evergreen coniferous forest, we examined the relationships between canopy phenology assessed by using the three indices and GPP determined from tower CO₂ flux observations, and we compared the camera-based indices with the corresponding spectra-based indices estimated by a spectroradiometer system. We found that (1) the three camera-based indices and GPP showed clear seasonal patterns in both forests; (2) the amplitude of the seasonal variation in the three camera-based indices was smaller in the evergreen coniferous forest than in the deciduous broad-leaved forest; (3) the seasonal variation in the three camera-based indices corresponded well to seasonal changes in potential photosynthetic activity (GPP on sunny days); (4) the relationship between the three camera-based indices and GPP appeared to have different characteristics at different phenological stages; and (5) the camera-based and spectra-based HUE indices showed a clear relationship under sunny conditions in both forests. Our results suggest that it might be feasible for ecologists to establish comprehensive networks for long-term monitoring of potential photosynthetic capacity from regional to global scales by linking satellite-based, in situ spectra-based, and in situ camera-based indices.

Introduction

To investigate terrestrial ecosystem structure and functions under climate change, it is crucial to understand the relationships between canopy phenological features such as leaf expansion or fall and photosynthetic productivity (Ito, 2010, Muraoka et al., 2010, Polgar and Primack, 2011, Richardson et al., 2010). In situ and satellite remote sensing are promising tools for observations of canopy phenology. An in situ camera system for obtaining canopy surface phenological images can be operated at low cost and consumes little electrical power, making deployment of such a system in different ecosystems at tower flux sites around the world convenient and practical, thus facilitating comparative analyses (Bater et al., 2011, Wingate et al., 2008). Recent studies have shown that the seasonal variations in the digital numbers of the red, green, and blue bands (RGB_DN) in phenological images obtained by digital cameras are correlated with those in tower-flux-based gross primary production (GPP) (Ahrends et al., 2009, Ide et al., 2011, Richardson et al., 2009, Sonnentag et al., 2011) and with those in net ecosystem exchange (Kurc and Benton, 2010); these relationships imply that it may be possible to estimate the temporal and spatial distributions of photosynthetic productivity from RGB_DN data on the basis of the relationship between RGB_DN and GPP (Baldocchi et al., 2005).

However, the relationship between seasonal variations in photosynthetic capacity, which reflect leaf area and pigments, and those in tower-flux-based GPP, which reflect actual photosynthetic activity, is not always linear. For instance, Nagai et al. (2010) reported that the Enhanced Vegetation Index observed in situ increased earlier than the tower-flux-based GPP during the leaf-expansion period in a deciduous broad-leaved forest. Other studies have reported that photosynthetic productivity shows large temporal variations, depending on weather conditions such as light, temperature, and vapor pressure, in various evergreen and deciduous forests (Lindroth et al., 1998, Malhi et al., 1998, Saigusa et al., 2002, Saitoh et al., 2010, Takanashi et al., 2005). As a result, the seasonal variation in RGB_DN is not always correlated linearly with the variation in actual photosynthetic activity (i.e., tower-flux-based GPP).

In this study, we examined the relationship between RGB_DN and GPP obtained by tower CO₂ flux observations at a daily time step over multiple years in a deciduous broad-leaved and an evergreen coniferous forest (the dominant forest types in East Asia) (Ito, 2008). However, to correctly detect leaf expansion and fall, we used three camera-based indices (i.e., the green excess index [GE], the green chromatic coordinate [rG], and HUE) instead of the individual RGB_DN values (Ide and Oguma, 2010, Richardson et al., 2007, Richardson et al., 2009, Sonnentag et al., 2012, Woebbecke et al., 1995). Our aim was to examine (1) the characteristics of seasonal variation in these camera-based indices and (2) the robustness of the relationship between tower flux-based GPP and the camera-based indices by assessing the relationship in two different forest ecosystems.