ABSTRACT Moso bamboo is an evergreen plant that extensively distributes in subtropical regions. Comparing to other forest types, Moso bamboo forest has some unique characteristics: high growth rate, short harvesting rotation, and on/off-year phenomenon. Plant phenology plays an important role in regulating carbon sequestration of the bamboo forest ecosystem. However, it is a challenge task to capture the phenological features of Moso bamboo forests on a regional scale due to frequent change of canopy structures and lack of high spatiotemporal remotely sensed data. The Vegetation and Environment monitoring on a New Micro-Satellite (VENµS) data with high spatiotemporal resolution provide the potential to examine the seasonal change of Moso bamboo forests. This research employs the VENµS time-series data (from January 2018 to December 2019) to analyse the spectral characteristics of on-year/off-year Moso bamboo forests and other two evergreen forest types (i.e., broadleaf forest and coniferous forest). The optimal spectral ranges for examining the seasonal variation of bamboo forests were determined. Three red-edge-based vegetation indices were reconstructed using the Harmonic analysis of time series (Hants) and compared. Red-edge position index (REPI) was selected to identify different phenological periods of Moso bamboo forests and other evergreen forest types. The results show that the spectral range of 730–920 nm in the VENμS data is sensitive to seasonal variation of Moso bamboo forests. The REPI can more effectively identify the two-year growing cycle of the bamboo forests than other vegetation indices, especially the bamboo shoots period. The start of the growing season of the off-year bamboo forest is approximately 50 to 60 days earlier than on-year bamboo forest. The results provided time-series phenological datasets of on-year and off-year Moso bamboo forests, which is valuable for local governments to conduct better ecological management and decision-making.

中文翻译：

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基于新微卫星（VENµS）时间序列数据的植被和环境监测研究竹林同年和反年的物候变化

摘要 毛竹是一种广泛分布于亚热带地区的常绿植物。与其他森林类型相比，毛竹林具有一些独特的特点：生长速度快，采伐轮伐期短，有开年/关年现象。植物物候在调节竹林生态系统固碳方面起着重要作用。然而，由于冠层结构的频繁变化和缺乏高时空遥感数据，在区域尺度上捕捉毛竹林的物候特征是一项具有挑战性的任务。对具有高时空分辨率的新微型卫星 (VENµS) 数据的植被和环境监测提供了检查毛竹林季节变化的潜力。本研究利用VENµS时间序列数据（2018年1月至2019年12月）分析了毛竹同年/非年间毛竹林和其他两种常绿林类型（即阔叶林和针叶林）的光谱特征。确定了检查竹林季节变化的最佳光谱范围。使用时间序列的谐波分析 (Hants) 重建三个基于红边的植被指数并进行比较。选择红边位置指数（REPI）来识别毛竹林和其他常绿林类型的不同物候期。结果表明，VENμS数据中730-920 nm的光谱范围对毛竹林的季节变化敏感。REPI比其他植被指数能更有效地识别竹林两年的生长周期，尤其是竹笋期。过年竹林的生长期开始比上年竹林提前约50至60天。研究结果提供了毛竹林同年和反年的时间序列物候数据集，对地方政府进行更好的生态管理和决策具有重要价值。