Phenology of Vegetation in Arid Northwest China Based on Sun-Induced Chlorophyll Fluorescence

Abstract

The accurate monitoring of vegetation phenology is critical for carbon sequestration and sink enhancement. Vegetation phenology in arid zones is more sensitive to climate responses; therefore, it is important to conduct research on phenology in arid zones in response to global climate change. This study compared the applicability of the enhanced vegetation index (EVI), which is superior in arid zones, and global solar-induced chlorophyll fluorescence (GOSIF), which has a high spatial resolution, in extracting vegetation phenology in arid zones, and explored the mechanism of the differences in the effects of environmental factors on the phenology of different vegetation types. Therefore, this study employed a global solar-induced chlorophyll fluorescence (GOSIF) dataset to determine the start and end of the vegetation growth season (SOSSIF and EOSSIF, respectively) in the arid zone of Northwest China from 2001 to 2019. The results were compared with those from the EVI-based MODIS climate product MCD12Q2 (SOSEVI and EOSEVI). Variations in the sensitivity of these climatic datasets concerning temperature, precipitation, and standardised precipitation evapotranspiration index (SPEI) were assessed through partial correlation analysis. Results: Compared to the MCD12Q2 climatic products, SOSSIF and EOSSIF closely matched the observed climate data in the study area. Spring onset was delayed at higher altitudes and latitudes, and the end of the growing season occurred earlier in these areas. Both SOSSIF and EOSSIF significantly advanced from 2001 to 2019 (trend degrees −0.22 and −0.48, respectively). Spring vegetation phenology was chiefly influenced by precipitation while autumn vegetation phenology was driven by both precipitation and SPEI. GOSIF-based climate data provides a more accurate representation of vegetation phenology compared to traditional vegetation indices. The findings of this study contribute to a deeper understanding of the potential ability of EVI and SIF to reveal the influence of vegetation phenology on the carbon cycle.

Keywords

• vegetation phenology
• GOSIF
• partial correlation analysis
• SPEI
• arid zone