Identification of plants responding to CO2 leakage stress using band depth and the full width at half maxima of canopy spectra

CCS (carbon capture and storage) is a technique that can effectively reduce CO2 emissions released into the atmosphere from industrial activities and mitigate global climate warming. However, the captured CO2 may leak from the underground storage, so a novel way of rapidly detecting points of CO2 leakage in sequestration fields is needed. A field experiment was performed at the Sutton Bonington Campus of the University of Nottingham (52.8 N, 1.2 W), and grass (cv Long Ley) and bean (Vicia faba cv Clipper) were chosen as the test plants. Sixteen plots, eight plots with grass and eight plots with bean, were established, and four of each plant was randomly chosen for the controlled injection of CO2 into the soil. The other plots acted as controls. The canopy spectra of the plants were measured, and the continuum removal method was used to process the spectral data. The spectral feature parameters of band depth and full width at half maxima of the canopy spectra were analysed, and the results showed that the band depth and full width at half maxima of the plants decreased with the elevation of CO2 leakage stress levels. Therefore, the product of band depth and full width at half maxima was defined as the Area index, which can better identify the plants under CO2 leakage stress throughout the entire growth period. To quantitatively evaluate the separability of the Area index, the Jeffries-Matusita distances were calculated among the Area indices of plants under different levels of CO2 leakage stress. The results suggested that the Area index can stably and reliably identify the plants under CO2 leakage stress. Therefore, in the future, the points of leakage on CCS projects can be detected by monitoring the growth of plants in the sequestration fields with hyperspectral remote sensing.