Vegetation carbon phenology products from 2001-2018

Xu, X.; Tang, Y.; Qu, Y.; Zhou, Z.; Hu, J. Global Vegetation Photosynthetic Phenology Products Based on MODIS Vegetation Greenness and Temperature: Modeling and Evaluation. Remote Sens. 2021, 13, 5080. https://doi.org/ 10.3390/rs13245080<br>Land surface phenology (LSP) products that are derived from different data sources havedifferent definitions and biophysical meanings. Discrepancies among these products and theirlinkages with carbon fluxes across plant functional types and climatic regions remain somewhatunclear. In this study, to differentiate LSP related to gross primary production (GPP) from LSPrelated to remote sensing data, we defined the former as vegetation photosynthetic phenology(VPP), including the starting and ending days of GPP (SOG and EOG, respectively). Specifically,we estimated VPP based on a combination of observed VPP from 145 flux-measured GPP sitestogether with the vegetation index and temperature data from MODIS products using multiplelinear regression models. We then compared VPP estimates with MODIS LSP on a global scale. Ourresults show that the VPP provided better estimates of SOG and EOG than MODIS LSP, with a rootmean square error (RMSE) for SOG of 12.7 days and a RMSE for EOG of 10.5 days. The RMSE wasapproximately three weeks for both SOG and EOG estimates of the non-forest type. Discrepanciesbetween VPP and LSP estimates varied across plant functional types (PFTs) and climatic regions. Ahigh correlation was observed between VPP and LSP estimates for deciduous forest. For most PFTs,using VPP estimates rather than LSP improved the estimation of GPP. This study presents a usefulmethod for modeling global VPP, investigates in detail the discrepancies between VPP and LSP, andprovides a more effective global vegetation phenology product for carbon cycle modeling than theexisting ones.<br>