Variations in Phenology Identification Strategies across the Mongolian Plateau Using Multiple Data Sources and Methods

Satellite data and algorithms directly affect the accuracy of phenological estimation; therefore, it is necessary to compare verify existing models identify optimal combination across Mongolian Plateau (MP). This study used five phenology fitting algorithms—double logistic (DL) polynomial (Poly) combined with dynamic threshold method at thresholds 35% 50% (DL-G35, DL-G50, Poly-G35, Poly-G50) DL cumulative curvature extreme value (DL-CUM)—and two types—the enhanced vegetation index (EVI) solar-induced chlorophyll fluorescence (SIF)—to start (SOS), peak (POS), end (EOS) growing season in alpine meadow (ALM), desert steppe (DRS), forest (FV), grassland (MEG), typical (TYG) MP. The methods for identifying SOS, POS, EOS areas were Poly-G50 (NSE = 0.12, Pbias 0.22%), DL-G35/50 −0.01, −0.06%), Poly-G35 0.02, 0.08%), respectively, based on SIF data. best −0.27, −1.49%), Poly-G35/50 −0.58, −1.39%), 0.29, −0.61%), EVI source explained most differences estimates. was significantly greater than that method, while all better SOS POS they EOS. Our findings can help facilitate establishment a estimation system suitable improve observation phenology.