Characterisation of functional-trait dynamics at high spatial resolution in a mediterranean forest from sentinel-2 and ground-truth data

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Abstract

The characterisation of functional-trait dynamics of vegetation from remotely sensed data complements the structural characterisation of ecosystems. In this study we characterised for the first time the spatial heterogeneity of the intra-annual dynamics of the fraction of absorbed photosynthetically active radiation (FAPAR) as a functional trait of the vegetation in Prades Mediterranean forest in Catalonia, Spain. FAPAR was derived from the Multispectral Instrument (MSI) on the Sentinel-2 satellite and validated by comparison with the ground measurements acquired in June 2017 at the annual peak of vegetation activity. The validation results showed that most of points were distributed along the 1:1 line, with no bias nor scattering: R 2 = 0.93, p < 0.05; with a root mean square error of 0.03 FAPAR (4.3%). We classified the study area into nine vegetation groups with different dynamics of FAPAR using a methodology that is objective and repeatable over time. This functional classification based on the annual magnitude (FAPAR-M) and the seasonality (FAPAR-CV) from the data on one year (2016-2017) complements structural classifications. The internal heterogeneity of the FAPAR dynamics in each land-cover type is attributed to the environmental and to the specific species composition variability. A spatial autoregressive (SAR) model for the main type of land cover, evergreen holm oak forest (Quercus ilex), indicated that topographic aspect, slope, height, and the topographic aspect x slope interaction accounted for most of the spatial heterogeneity of the functional trait FAPAR-M, thus improving our understanding of the explanatory factors of the annual absorption of photosynthetically active radiation by the vegetation canopy for this ecosystem.

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Schauman, S., Verger, A., Filella, I., & Peñuelas, J. (2018). Characterisation of functional-trait dynamics at high spatial resolution in a mediterranean forest from sentinel-2 and ground-truth data. Remote Sensing, 10(12). https://doi.org/10.3390/rs10121874

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