以PhenoCam分析台北植物園荷花池水生植物之物候變化

傳統物候學的調查與監測，需要密集的人工觀察與記錄，但資料獲得常礙於時間和人力有所限制，本研究利用林業試驗所生態感測開放資料平台所蒐集的自動攝影相機所拍攝影像，以PhenoCam軟體進行綠度座標指數（Green chromatic coordinate, GCC）與紅度座標指數（Red chromatic coordinate, RCC）判識，分析台北植物園荷花池於2014－2020年間水生植物的物候變化。結果顯示，以7年長時間而言，GCC可反應主要水生植物荷花（Nelumbo nucifera）隨著季節的生長變化，RCC則反應荷花葉片凋萎的變化；以分年期而言，GCC變化可分為2類型，分別為2015、2017、2018年的窄單峰類型，以及2014、2016、2019、2020的波動寬峰類型。窄單峰係為主要水生植物荷花隨季節消長之物候變化，而波動寬峰類型則是在荷花枯萎後，另由其他水生植物佔據。廣義線性模型檢測分析結果顯示，氣溫是荷花池GCC的主要影響因子。GCC及RCC出現的高峰期以及細部變化在各年間有差異，除氣溫的影響外，亦受到荷花池人為經營管理強度影響。

關鍵字

PhenoCam ；綠度座標指數；紅度座標指數；物候；荷花

並列摘要

Traditional phenology collections relied on intensive observation and recording, but good quality data is often limited by time and manpower. This study aims to analyze aquatic plant phenology from the automatic camera of the lotus pond in Taipei Botanical Garden during 2014 - 2020. The green chromatic coordinate (GCC) and red chromatic coordinate (RCC) were both calculated to interpret the phenological patterns of Nelumbo nucifera via the PhenoCam software. The results collected over 7 years showed that the variation of GCC reflected the growing season of lotus (Nelumbo nucifera), and the variation of RCC reflected the leaf withering season of lotus. The annual variation of GCC can be divided into two groups: the narrow peak groups in 2015, 2017 and 2018, and the wide peak groups in 2014, 2016, 2019 and 2020. The narrow peak groups represented the growing season of the lotus, while the wide peak groups represented other aquatic plants that occupied the pond after the lotus died. The results of the generalized linear model analysis showed that the temperature had great influence on the annual variation of GCC. In addition, the variation of GCC and RCC in the Lotus pond were also affected by the intensity of human management.

並列關鍵字

PhenoCam ； phenology ； green chromatic coordinate ； red chromatic coordinate ； Nelumbo nucifera

主題瀏覽