An Optical Sensor Network for Vegetation Phenology Monitoring and Satellite Data Calibration
AbstractWe present a network of sites across Fennoscandia for optical sampling of vegetation properties relevant for phenology monitoring and satellite data calibration. The network currently consists of five sites, distributed along an N-S gradient through Sweden and Finland. Two sites are located in coniferous forests, one in a deciduous forest, and two on peatland. The instrumentation consists of dual-beam sensors measuring incoming and reflected red, green, NIR, and PAR fluxes at 10-min intervals, year-round. The sensors are mounted on separate masts or in flux towers in order to capture radiation reflected from within the flux footprint of current eddy covariance measurements. Our computations and model simulations demonstrate the validity of using off-nadir sampling, and we show the results from the first year of measurement. NDVI is computed and compared to that of the MODIS instrument on-board Aqua and Terra satellite platforms. PAR fluxes are partitioned into reflected and absorbed components for the ground and canopy. The measurements demonstrate that the instrumentation provides detailed information about the vegetation phenology and variations in reflectance due to snow cover variations and vegetation development. Valuable information about PAR absorption of ground and canopy is obtained that may be linked to vegetation productivity. View Full-Text
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Eklundh, L.; Jin, H.; Schubert, P.; Guzinski, R.; Heliasz, M. An Optical Sensor Network for Vegetation Phenology Monitoring and Satellite Data Calibration. Sensors 2011, 11, 7678-7709.
Eklundh L, Jin H, Schubert P, Guzinski R, Heliasz M. An Optical Sensor Network for Vegetation Phenology Monitoring and Satellite Data Calibration. Sensors. 2011; 11(8):7678-7709.Chicago/Turabian Style
Eklundh, Lars; Jin, Hongxiao; Schubert, Per; Guzinski, Radoslaw; Heliasz, Michal. 2011. "An Optical Sensor Network for Vegetation Phenology Monitoring and Satellite Data Calibration." Sensors 11, no. 8: 7678-7709.