A New Change Point Estimation of Forest Photosynthetic Phenology Method Based on the Maximum Perpendicular Distance Using Solar-Induced Chlorophyll Fluorescence

Forests play a crucial role in regulating the carbon balance and maintaining global climate stability. Remote sensing has provided new perspectives for regional monitoring of vegetation phenology. However, an accurate method for extracting the photosynthetic phenology of forests remains challenging. This study proposes an innovative method, the change point estimation of forest photosynthetic phenology method based on the maximum perpendicular distance (CBPD). CBPD extracted the dates of the start of the season (SOS) and the end of the season (EOS) for forests in North America from solar-induced chlorophyll fluorescence and daily flux tower observations. The validation results of CBPD indicated that compared to those of the double-logistic, first-order derivative, and dynamic threshold methods, the root mean square error of CBPD decreased by 0.04 to 14.04 d, while Pearson’s correlation coefficient and agreement index increased by 0.03 to 0.30 and by 0.34 to 21.52, respectively. Furthermore, CBPD demonstrated substantial consistency ( P < 0.01) with cross-validation based on remote sensing of photosynthetic phenology. In addition, SOS exhibited greater interannual variability compared to EOS. SOS was dominated by air temperature in 93.89% of the forest area. EOS was dominated by radiation in 48.70% of the forest area. In summary, CBPD has a great potential for tracking forest photosynthetic phenology, offering crucial insights into phenological responses to climate variations.