Supporting data for “Monitoring and understanding fine-scale phenological variability in temperate forests”

For my PhD thesis, I have utilized a range of data from various sources.1). I utilized time-series PlanetScope data with a 3 m spatial resolution from the Planet Labs Inc. to generate phenological maps for six temperate forest sites within the National Ecological Observatory Network (NEON). The derived phenological maps can be used to monitor plant phenology at fine scales.2). I used ground records of plant phenology for six temperate forest sites to validate PlanetScope-derived phenological metrics. These data are publicly available in the data repository of NEON. Detailed phenophase status and intensity are recorded for a number of individual trees, which can be used to derive the timing of key phenological events.3). Maps of seven foliar traits and five structural traits for four NEON temperate forest sites were also used. Foliar traits include leaf mass per area (LMA), carbon content, nitrogen content, area-based chlorophyll concentration, phenolics concentration, starch concentration, and ẟ¹³C. Structural traits include canopy height, plant area index (PAI), height skew, entropy, and rugosity. These traits are derived from remote sensing data, provide detailed characterizations of plant attributes.4). I utilized time-series satellite imagery from harmonized Landsat and Sentinel-2 data to generate maps of interannual phenological variability for four NEON temperate forests sites. The derived maps offer a visualization of the patterns of interannual phenological variability at the site level. By integrating these maps with functional trait data, further investigations can be conducted to explore the underlying biotic drivers of the variability.Overall, the combination of these data provided a comprehensive dataset for my thesis, allowing for a thorough investigation of the patterns of phenological variability and its underlying drivers. <br>