B53C-0198:
Optical Sensing of Ecosystem Carbon Fluxes Combining Spectral Reflectance Indices with Solar Induced Fluorescence

Friday, 19 December 2014
Karl F Huemmrich1, Elizabeth Middleton1, Lawrence A Corp2, Petya K Campbell3 and William P Kustas4, (1)NASA Goddard Space Flight Cen., Greenbelt, MD, United States, (2)Sigma Space Corporation, Lanham, MD, United States, (3)UMBC, Greenbelt, MD, United States, (4)USDA ARS, Beltsville, MD, United States
Abstract:
Optical sampling of spectral reflectance and solar induced fluorescence provide information on the physiological status of vegetation that can be used to infer stress responses and estimates of production. Multiple repeated observations are required to observe the effects of changing environmental conditions on vegetation. This study examines the use of optical signals to determine inputs to a light use efficiency (LUE) model describing productivity of a cornfield where repeated observations of carbon flux, spectral reflectance and fluorescence were collected. Data were collected at the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) fields (39.03°N, 76.85°W) at USDA Beltsville Agricultural Research Center. Agricultural Research Service researchers measured CO2 fluxes using eddy covariance methods throughout the growing season. Optical measurements were made from the nearby tower supporting the NASA FUSION sensors. The sensor system consists of two dual channel, upward and downward looking, spectrometers used to simultaneously collect high spectral resolution measurements of reflected and fluoresced light from vegetation canopies. Estimates of chlorophyll fluorescence, combined with measures of vegetation pigment content and the Photosynthetic Reflectance Index (PRI) derived from the spectral reflectance are compared with CO2 fluxes over diurnal periods for multiple days. PRI detects changes in Xanthophyll cycle pigments using reflectance at 531 nm compared to a reference band at 570 nm. The relationships among the different optical measurements indicate that they are providing different types of information on the vegetation and that combinations of these measurements provide improved retrievals of CO2 fluxes than any index alone.