A new dataset provides high-resolution, spatially-contiguous, global solar-induced chlorophyll fluorescence (SIF) estimates (mW/m2/nm/sr) at 0.05 degree spatial and 16-day temporal resolution beginning in September 2014 and continuing into the present. This product was derived by training an artificial neural network (ANN) on Orbiting Carbon Observatory-2 (OCO-2) SIF observations and MODIS Bidirectional Reflectance Distribution Function (BRDF)-corrected seven-band surface reflectance along the OCO-2 orbits.
SIF is an optical signal that is emitted from vegetation when sunlight activates photosynthesis, and measures of SIF can serve as a functional proxy for photosynthetic rate. The high resolution and global contiguous coverage of this dataset will greatly enhance the synergy between satellite SIF and photosynthesis measured on the ground. SIF has a strong positive correlation with gross primary productivity, and the measure could dramatically improve estimates of terrestrial photosynthesis. Potential applications of this dataset include advancing dynamic drought monitoring and mitigation, informing agricultural planning and yield estimation, and providing a benchmark for upcoming satellite missions with SIF capabilities at higher spatial resolutions.
Data Citation: Yu, L., J. Wen, C.Y. Chang, C. Frankenberg, and Y. Sun. 2019. High Resolution Global Contiguous SIF Estimates Derived from OCO-2 SIF and MODIS. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1696
Data Center: ORNL DAAC