Identify and track white flower and leaf phenology of deciduous broadleaf trees in spring with time series PlanetScope images

Abstract

In spring, many deciduous broadleaf trees start with flower emergence and then leaf emergence, which are two key phenological events, as they signal the onset of reproduction and vegetative growth in a year. These trees provide essential resources for early pollinators searching for flowers, contribute to biodiversity, and create socio-economic benefits through tourism. Accurate detection and monitoring of the flower and leaf phenology of these trees are important. In this study we combine in-situ photo observations with time series satellite data in spring 2024 to develop new methods for identifying and tracking white flower and leaf phenology of Callery Pear trees, which are deciduous broadleaf trees distributed worldwide. We analyzed in-situ photos and surface reflectance, flower-related, and leaf-related vegetation indices from three optical satellite datasets—PlanetScope (3-m, daily), Sentinel-2 A/B (10-m, 5-day), and Harmonized Landsat and Sentinel-2 (HLS, 30-m, 2–3-day; HLSL30 and HLSS30). Time series of White Flower Index (WFI), a combination of blue, green, and red bands, delineated the flowering period (start, peak, and end dates) of white (light-colored) flowers. Time series of chlorophyll and green leaf indicator (CGLI; Blue < Green > Red) delineated the green leaf emergence dates of the trees (start of season, SOS). In comparison, flower and leaf phenology of these trees cannot be accurately identified and tracked by Sentinel-2 data due to insufficient number of good-quality observations and HLS data due to mixed land cover types in 30-m pixels. This study enhances our understanding of surface reflectance dynamics of flowers and green leaves of these trees in spring and demonstrates the critical role of satellite data with high spatio-temporal resolutions and WFI and CGLI algorithms in tracking floral and leaf phenology.