Sensing of Photosynthetic Activity of Crops
The light use efficiency of photosynthesis dynamically adapts to environmental factors and is one major factor determining crop yield. Optical remote sensing techniques have the potential to detect physiological and biochemical changes in plant ecosystems, and non-invasive detection of changes in photosynthetic energy conversion may be of great potential for managing agricultural production in a future bio-based economy. Here we give an overview on the principles of optical remote sensing in crop systems with a special emphasis on investigating hyperspectral reflectance data and the sun-induced fluorescence signal. Especially sun-induced fluorescence as a parameter, which becomes important in remote sensing research may have great potential quantifying the physiological status of the photosynthetic apparatus. Both remote sensing principles were applied during the CEFLES2 campaign in Southern France, where the structural and functional status of several crops was measured on the ground and using state-of-the-art optical remote sensing techniques. Sun-induced fluorescence measurements over a variety of crops showed that additional information can be retrieved also over dense canopies, where classical remote sensing signals often saturate. With a view to the future, we discuss how hyperspectral reflectance and sun-induced fluorescence can quantitatively be related to photosynthetic efficiency and help to measure and manage productivity of natural and agricultural ecosystems.
This work has been made possible by the funding support of the ESA-projects (1) Technical Assistance for Airborne/Ground Measurements in support of Sentinel-2 mission during CEFLES2 Campaign (ESRIN/Contract No. 20801/07/I-LG) (2) Technical Assistance for Airborne/Ground Measurements in support of FLEX mission proposal during CEFLES2 Campaign (ESRIN/Contract No. 20802/07/I-LG) (3) FLEX Performance analysis and requirements consolidation study (ESTEC/Contract No. 21264/07/NL/FF). Additional financial and intellectual support was provided by the SFB/TR 32 ‘Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation’ – project D2, funded by the Deutsche Forschungsgemeinschaft (DFG).
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