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Urban trees that provide essential ecosystem services are exposed to multiple stress factors. Moreover, climate predictions indicate that the frequency and severity of drought events will increase, which can lead to tree defoliation, greater sensitivity to pests and pathogens, and thus higher tree mortality. Remote sensing data have been used to identify the effects of stress factors on the dynamics of urban trees at a large scale, but the coarse spatial resolution of the data make it impossible to differentiate species that suffer from stress from those that are more resilient. This study focused on dynamics of trees in Rennes (France) at a fine spatial resolution (10 and 20 m) using Sentinel-2 time series. We analysed five tree species for two years with contrasting weather conditions (2021 and 2022) along an urban-rural gradient. Vegetation dynamics were monitored using two vegetation indices (ARVI and OSAVI) and two vegetation traits (leaf area index (LAI) and leaf chlorophyll content (LCC)). Phenological, productivity, and disturbance metrics were derived from these time-series. The relationships between these metrics and stress factors (drought, urban conditions) were analyzed. The results revealed a longer growing season and maturity period for four species in 2022 (the drier year). Productivity metrics varied: some species grew less under drought, whereas others, such as Platanus acerifolia, grew more, suggesting potential resilience mechanisms. Disturbance levels were higher in 2022, indicating higher stress condition. Urban intensity generally correlated with longer growing seasons and altered productivity dynamics. This study emphasizes the value of Sentinel-2 time series for supporting urban tree management and policy decisions under changing environmental conditions.
Saint et al. (Thu,) studied this question.