Abstract Bud and leaf development are important phenological events and help in defining the growing period of trees. Canopy greenness derived from PhenoCam has been used to investigate leaf phenology. Questions remain on how much the continuous records of canopy greenness represent bud developmental phases, and how growing period boundaries are related to canopy greenness and bud phenology. In this study, we compared bud phenology of black spruce [Picea mariana (Mill.) B.S.P] during 2015, 2017 and 2018 with the canopy greenness, represented by Green Chromatic Coordinate (GCC), derived from PhenoCam images of a boreal stand in Quebec, Canada. Logit models were applied to estimate the probability of observing sequential phenological phases of bud burst and bud set along with GCC. GCC showed a bell-shaped pattern, with a slow increase in spring, a peak in summer and a gradual decrease in autumn. The start and end of budburst, and bud set, occurred when GCC reached 72% and 92% (spring), and 94% (autumn) of its maximum amplitude, respectively. These GCC values are reliable thresholds indicating the growing period boundaries. Our study builds a bridge between phenological observations and automatic near-surface remote sensing, providing a statistically sound protocol for calibrating PhenoCam with field observations.

中文翻译：

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用黑云杉支架的物候观察校准 PhenoCam 数据

摘要 芽叶发育是重要的物候事件，有助于确定树木的生长期。源自 PhenoCam 的冠层绿度已被用于研究叶片物候学。关于冠层绿度的连续记录在多大程度上代表芽发育阶段以及生长期边界如何与冠层绿度和芽物候相关的问题仍然存在。在这项研究中，我们比较了 2015、2017 和 2018 年黑云杉 [Picea mariana (Mill.) BSP] 的芽物候与树冠绿度，以绿色色坐标 (GCC) 表示，来自魁北克北方林分的 PhenoCam 图像， 加拿大。应用 Logit 模型来估计观察芽破裂和芽集以及 GCC 的连续物候阶段的概率。GCC呈钟形形态，春季缓慢上升，夏季达到高峰，秋季逐渐减少。萌芽和萌芽的开始和结束发生在 GCC 分别达到其最大振幅的 72% 和 92%（春季）和 94%（秋季）时。这些 GCC 值是指示生长期边界的可靠阈值。我们的研究在物候观测和自动近地表遥感之间架起了一座桥梁，为通过实地观测校准 PhenoCam 提供了统计上合理的协议。