Seasonal Divergence of Topographic Effects on Nirv-Derived Photosynthetic Phenology in a Mountainous Forest

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, the influence of topography on NIRv induces uncertainty in photosynthetic phenology retrieval over mountainous areas. We evaluated the topographic effects on NIRv and employed topographically corrected NIRv (TCNIRv) to improve its phenology retrieval accuracy over a mountainous forest. We extracted the start/end of the photosynthetically active season (SOS/EOS) from the NIRv and TCNIRv time series, and compared them with those generated from in-situ gross primary production (GPP) measured at the Lägeren flux tower. We observed a seasonally divergent performance of NIRv in photosynthetic phenology extraction: NIRv-derived SOS had a good consistency with GPP-derived estimates (113d vs 114d from NIRv and GPP, respectively), whilst EOS obviously lagged GPP-derived ones (292d vs 268d from NIRv and GPP, respectively). The seasonal divergence of NIRv-derived photosynthetic phenology might be related to the contrasting velocities of the magnitude of topographic effects on NIRv around SOS and EOS. In contrast, TCNIRv reduced topographic effects in the original NIRv and it was comparable to GPP in estimating SOS/EOS. As such, we suggest that topographic effects should be eliminated when using NIRv for 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 over complex topography mountainous areas.

Keywords: Photosynthetic phenology, topographic effects, near-infrared reflectance of vegetation (NIRv), topographically corrected NIRv (TCNIRv), seasonal divergence