## 4 Discussion  
At the leaf scale, the results show that CIgreen has a strong correlation with variation in leaf chlorophyll content from a wide range of species and leaf development stages (Figure 4). This result agrees with that of [PERSON] _et al._[50], who demonstrated a wide range of leaf greenness and found that the maximum sensitivity of the reflectance coincides with green absorption. The green wavelength range was also reported to be superior for determining chlorophyll content in eight crops [69]. VI based on red reflectance (680 nm) was largely insensitive to variation in chlorophyll content. For most leaves, when light enters the upper surface of a leaf, blue light and red light are absorbed by chloroplasts near the irradiated surface, owing to strong absorption bands of chlorophyll in the blue and red regions of the spectrum. Because blue overlaps with the absorption of carotenoids, it is not generally used for estimation of chlorophyll content [57]. The green band wavelength of SGLI ranges from 520 to 540 nm, and the spectral reflectance around 520 nm is determined not only by chlorophyll-a and chlorophyll-b absorption, but also by carotenoid absorption [24]. However, the pigments contributing most to light absorption in the PAR region are those that are intimately involved in photosynthesis, namely, chlorophyll a and b and carotenoids [70]. Moreover, during the growing season as the chlorophyll content in leaves increases, the spectral features of carotenoids diminish owing to the strong and overlapping absorption by chlorophyll [71]. Therefore, the green band of SGLI can serve as a good representative wavelength for estimating leaf chlorophyll content. Because leaf chlorophyll content increases toward the middle of a leaf [48] and because green light penetrates deeper into the leaf, green reflected light is decreased by chlorophyll content absorption. Thus, green reflected light is very effective for detecting chlorophyll content and can represent leaf photosynthesis. To select an appropriate VI for estimating chlorophyll content, we chose CIgreen because NIR is insensitive to chlorophyll content and the ratio between the insensitive and sensitive bands can minimize the variations in leaf-scattering properties [72]. Furthermore, the reflectance of NIR and green wavelengths has a strong linear correlation with chlorophyll content [72; 73; 74]. Therefore, CIgreen is suitable for estimating leaf chlorophyll content. [PERSON] and [PERSON] [75] found that the chlorophyll concentration of sun-exposed canopy was closely related to both leaf and canopy photosynthetic capacity in a Douglas fir canopy in a controlled environment. The correlation coefficient for sun-exposed canopy was higher than that for shaded canopy. Moreover, the NDVI calculated using a narrow green band (565-575 nm) was best correlated with photosynthesis potential under sunlight. Thus, it is possible to estimate the photosynthetic capacity of a sun-exposed canopy by integrating the leaf photosynthetic capacity. At the canopy and satellite scales, Pmax_capacity2000 was used instead of the canopy chlorophyll content because chlorophyll content within a vegetation canopy is positively related to the productivity of that vegetation [31]. To obtain Pmax_capacity from the light-response curve, some researchers have applied a non-rectangular hyperbolic equation [46, 76, 77, 78] with three main parameters: initial slope, Pmax, and convexity. A non-rectangular hyperbola yielded a better fit than a rectangular hyperbola equation with only two parameters (initial slope and Pmax). However, we chose to use a rectangular hyperbola (Equation (1)) to obtain Pmax_capacity with constant \(\alpha_{\text{slope}}\) to simplify the methodology and minimize the number of parameters [79, 80, 81, 82]. Our results demonstrate the applicability of the rectangular hyperbola using constant \(\alpha_{\text{slope}}\) for calculating Pmax_capacity2000 for each plant functional type.