Canopy near-infrared reflectance and terrestrial photosynthesis

A model is only as good as the data that go into it (garbage in, garbage out), so any effort to improve remote sensing data will contribute to better global models. Badgley et al. describe a new parameter, near-infrared reflectance of vegetation (NIR_V), that more accurately quantifies photosynthesis at the global scale (Gross Primary Productivity, GPP) from satellite sensor data. NIR_V combines total near-infrared reflectance (NIR_T) and the normalized difference vegetation index (NDVI), so therefore “NIR_V represents the proportion of pixel reflectance attributable to the vegetation in the pixel.” The authors show that NIR_V shows a closer correlation to GPP than solar-induced chlorophyll fluorescence (SIF). Science Adv. 10.1126/sciadv.1602244