Abstract
Accurate estimation of photosynthetic phenology is of great importance for understanding the response of terrestrial biosphere to climate change. The near-infrared reflectance of vegetation (NIRv) has been increasingly used to estimate photosynthetic phenology. However, topography significantly affects illumination conditions and induces uncertainty in the retrieval of NIRv photosynthetic phenology over mountainous areas. We evaluated the illumination effects on three modalities of NIRv: (i) the original NIRv, (ii) the product of NIRv and solar incident radiation (NIRvP), and (iii) the topographically corrected NIRv (TCNIRv). We assessed the impact of sun geometry on the phenological metrics for the timing of the start and end of the season (i.e., SOS and EOS) derived from satellite NIRv time series as compared with those derived from in-situ gross primary production (GPP) measured at the Brasschaat (BE-Bra) and Lägeren (CH-Lae) flux towers located, respectively, over a flat and a mountainous forest area in Europe. We observed a seasonally divergent performance of NIRv in photosynthetic phenology extraction: NIRv-derived SOS had a good consistency with GPP-derived estimates (109/114d for NIRv vs 108/115d for GPP at BE-Bra/CH-Lae), whilst it showed a positive time lag for the EOS (291/292d for NIRv vs 264/268d for GPP at BE-Bra/CH-Lae). The radiation constraint in NIRvP formulation corrected the bias in NIRv-based EOS estimates. Path length correction (PLC) also alleviates the illumination effects on the original NIRv, making TCNIRv comparable to NIRvP in estimating SOS and EOS. We conclude that illumination effects must be corrected from NIRv for the extraction of photosynthetic phenology, especially for the autumn phenology. Our study has significant implications for understanding the responses of phenology to climate change and the climate-carbon feedbacks, particularly over complex topography mountainous areas.
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