Assessment of plant health and productivity is vital to ensure future food security of the global population under a changing climate. Chlorophyll fluorescence (CF), a signal emitted by green plants, can reveal this information. Although CF has revolutionised photosynthetic research, current measurements are limited to individual plants. Remote sensing of canopy CF is required for efficient management of agricultural crops, forests, and natural ecosystems and is crucial for accurate estimation of plant carbon assimilation and production. This project will deliver remote sensing technology to bridge the gap between leaf and canopy productivity and pave the way for understanding both artificial and solar induced canopy CF measured from space.
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Sun-induced fluorescence (SIF)
The uptake and release of CO2 by plants are critical components of the global carbon budget. Since the earth atmosphere’s CO2 levels have risen rapidly since the industrial revolution, it is important to monitor the potential of plant material as a net sink of atmospheric CO2. Photosynthesis is the key process that removes CO2 from the atmosphere. Changes in gross photosynthesis have major impacts on the global carbon cycle (ESA, 2015).
But changes in photosynthesis are not only significant on a global scale. The process of turning water, light, nutrients and CO2 into energy has also local impact on plant growth and productivity. Photosynthetic productivity changes rapidly and is highly responsive to plant stress. A way to monitor photosynthetic activity is measuring Sun-Induced Fluorescence (SIF).
When plants are exposed to sunlight, they reflect, transmit, and absorb light. In addition, they re-emit light in a different wavelength and that is fluorescence. The majority, about 80%, of the absorbed light is used in photochemistry (for photosynthesis) while the rest is dissipated as heat or re-emitted as fluorescence. Therefore, the amount of fluorescence emission is a direct indicator of the photosynthetic activity of a plant.
Analysing SIF more closely, it originates from the photosystem (PSI) and photosystem II (PSII) within the leaves. The PSII is responsible for SIF emission in the far red to near infrared between 650-780 nm (peak at 685 nm) while the PSI only emits in wavelengths >700 nm with a peak at 740 nm (ESA, 2015). The position of the two emission peaks plays an import role in the SIF measurement.
The SIF signal is superimposed on the signal from the reflected light of the vegetation. Furthermore, the amount of SIF is small (1% of the absorbed light) compared to the reflected light, hence it is difficult to decouple the two signals. This problem can be overcome by measuring inside and outside of distinct, narrow absorption features of the atmosphere, so called Fraunhofer Lines. For SIF retrieval, we utilise the O2-B absorption band at 680 nm and the O2-A absorption band at 760 nm. There are multiple Fraunhofer Line Discrimination (FLD) methods that are based on comparing the energy flux from the vegetation to the energy flux from the sun. The amount of SIF is derived from ratio equations using the signals inside and outside the absorption band as input (Liu et al., 2005). Since the absorption bands are only a few nanometres wide, it is crucial to delineate those features with a high spectral resolution sensor.
UAS SIF measurements
The spatial and spectral accuracy of UAS SIF measurements is crucial for their validity. Measuring SIF from an Unmanned Aerial Vehicle (UAV) requires very high spectral resolution of the sensor (~ 1 nm) and the system needs to be calibrated for the changing irradiance conditions at short intervals.
Thus, we are using a high performance QEPro Ocean Optics spectrometer for our measurements. The QEPro is configured with two channels to measure the downwelling irradiance and the upwelling radiance. Switching between the channels allows us to capture the radiance from the vegetation target as well as the irradiance from the sun.
Highly accurate georeferencing of the UAV is the second crucial component for UAS SIF measurements with a non-imaging spectrometer. Knowing the exact position and orientation of the sensor is needed to determine the spectrometer footprint on the ground and thus identifying the measurement target. Therefore, we directly georeference the spectrometer readings by synchronising them with an Inertial Measurement Unit (IMU) as well as with a machine vision camera. The QEPro spectrometer, the IMU, and the machine vision camera are installed on a gimbal. To maximise the measurement precision, we correct for the boresight alignment between IMU, QEPro, and machine vision camera.
SIF – Related projects
Measuring SIF from a UAV platform will contribute to the understanding of the SIF signal on different spatial scales. On a regional scale, the Hyplant airborne sensor enables collecting high resolution SIF imagery. The collective knowledge from those two platforms is crucial for the upcoming fluorescence explorer (FLEX) satellite mission that will be launched in 2022. The FLEX mission will provide global maps of SIF emission to provide a tool for early plant stress monitoring, improve estimates of Gross Primary Production (GPP) and enhance the understanding of global carbon and water cycles.
ESA (2015). Report for Mission Selection: FLEX. ESA SP-13330/2 (2 volume series), European Space Agency, Noordwijk, The Netherlands.
Liu, L., Zhang, Y., Wang, J., Zhao, C. (2005). Detecting solar-induced chlorophyll fluorescence from field radiance spectra based on the Fraunhofer line principle. IEEE Trans. Geosci. Remote Sens. 43, 827–832. doi:10.1109/TGRS.2005.843320