Can land surface phenology from Sentinel-2 time-series be used as an indicator of Macaronesian ecosystem dynamics?

Abstract

Land surface phenology (LSP), the study of phenological patterns of vegetation using vegetation index (VI) time-series derived from multi-spectral satellite imagery, has helped to improve the understanding of the seasonal dynamics of terrestrial ecosystems from local to global scale. High spatial resolution satellite observations have emerged as a new possibility for monitoring the seasonal dynamics of heterogeneous ecosystems. Under-studied Macaronesian ecosystems have specific characteristics that make LSP estimation a complex task (e. g., frequent cloud cover, frequent presence of atmospheric aerosols, different degrees of vegetation density, diversity of plant species, landscape heterogeneity). Thus, this study aims to analyse the potential of LSP based on Sentinel-2 data to monitor the phenological dynamics of vegetation in the Macaronesian ecosystems of Canary Islands (Spain). NDVI time-series were generated using Sentinel-2 data from January 2018 to December 2021. NDVI time-series were smoothed using double logistic function. Three phenometrics, such as the start of the growing season (SOS), the end of the growing season (EOS) and the length of the growing season (LOS), were extracted using a threshold-based method (20%) only for pixels where the mean NDVI value of the smoothed four-year time-series was higher than 0.2. Growing season of the major of Macaronesian vegetation started between late summer and late autumn (start of the wet season) and ended between early spring and early summer (end of the wet season). The most representative Macaronesian tree species had a clear and marked seasonality, except for the laurel forest species. SOS of Juniperus phoenicea subsp. turbinata was slightly later than for Olea europaea var. sylvestris and Pinus canariensis, while the mean EOS was slightly later for Olea europaea var. sylvestris. The intra-specific variability of SOS and EOS in the laurel forests was very high. LSP derived from Sentinel-2 data contributed to understand the seasonal dynamics of the main Macaronesian ecosystems. However, the heterogeneity of laurel forests made it difficult the LSP estimation in laurel forests. Thus, complementary phenological approaches are suggested to improve the knowledge of the seasonal dynamics of this Macaronesian ecosystem.