Estimation of daily FAPAR from MODIS instantaneous observations at forest sites

Abstract

The daily Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is crucial for vegetation dynamics monitoring and terrestrial carbon modeling. However, current FAPAR products only provide instantaneous values at the satellite transit times and a large data gap exists between instantaneous and daily FAPAR. To fill this gap, this study aimed to estimate daily FAPAR from instantaneous values retrieved from Moderate-resolution Imaging Spectroradiometer (MODIS) data. A framework combining method to estimate instantaneous FAPAR (instantaneous FAPAR method) and method to calculate daily FAPAR (instantaneous-to-daily FAPAR method) was proposed. Instantaneous FAPAR method for estimating intra-daily FAPAR from reduced observations was evaluated. Three instantaneous-to-daily FAPAR methods (ratio, simple average and solar zenith angle weighted average methods) were compared to estimate the daily FAPAR from continuous instantaneous values. The daily FAPAR was finally estimated from MODIS instantaneous values. The estimation and validation were performed at seven forest sites distributed in North America and Western Europe.The results show that the instantaneous FAPAR method can accurately simulate the intra-daily instantaneous FAPAR (RMSE ∼ 0.01, bias ∼ 0). The three instantaneous-to-daily FAPAR estimation methods showed similar performances (R2 ∼1, RMSE ∼ 0.01, and bias ∼ 0). The in situ instantaneous FAPAR values at the MODIS acquisition times underestimated the daily value during the non-peak growing season (FAPAR < 0.9) and the underestimation is also affected by the diffuse PAR radiation. MODIS instantaneous FAPAR underestimates in situ daily FAPAR over the year. The daily FAPAR estimates from in situ instantaneous values at MODIS acquisition times or the MODIS instantaneous FAPAR data reduce the gap between instantaneous and daily values. Validated by in situ data, the MODIS instantaneous FAPAR products should be further optimized to improve the accuracy of daily FAPAR estimation. This study lays the foundation for estimating the daily FAPAR from instantaneous values to improve GPP estimation.