Comparison of Phenological Parameters Extracted from SIF, NDVI and NIRv Data on the Mongolian Plateau - Cha Ersi; Tubuxin Bayaer; Yuhai Bao; Yulong Bao; Mei Yong; Quan Lai; Xiang Zhang; Yusi Zhang (Remote Sensing, 2022)
The phenological parameters estimated from different data may vary, especially in response to climatic factors. Therefore, we estimated the start of the growing season (SOS) and the end of the growing season (EOS) based on sunlight-induced chlorophyll fluorescence (SIF), the normalized difference vegetation index (NDVI) and the near-infrared reflectance of vegetation (NIRv). The SIF, NDVI and NIRv breakpoints were detected, and the trends and change-points of phenological parameters based on these data were analyzed. The correlations between the phenological parameters and snow-related factors, precipitation, temperature, soil moisture and population density were also analyzed. The results showed that SIF and NIRv could identify breakpoints early. SIF could estimate the latest SOS and the earliest EOS. NDVI could estimate the earliest SOS and the latest EOS. The change-points of SOSSIF were mostly concentrated from 2001 to 2003, and those of SOSNDVI and SOSNIRv occurred later. The change-points of EOSSIF and EOSNIRv were mostly concentrated from 2001 to 2007, and those of EOSSIF occurred later. Differently from the weak correlation with SOSSIF, SOSNDVI and SOSNIRv were significantly correlated with snow-related factors. The correlation between the meteorological factors in the summer and autumn and EOSSIF was the most significant. The population density showed the highest degree of interpretation for SOSNIRv and EOSNDVI. The results reveal the differences and potentials of different remote-sensing parameters in estimating phenological indicators, which is helpful for better understanding the dynamic changes in phenology and the response to changes in various influencing factors.