Hyperspectral remote sensing as a monitoring tool for geologic carbon sequestration

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Montana State University - Bozeman, College of Agriculture


The contemporary global climate crisis demands mitigation technologies to curb atmospheric greenhouse gas emissions, principally carbon dioxide (CO 2). Geologic carbon sequestration (GCS) is a method by which point source CO 2 emissions are purified and deposited in subsurface geologic formations for long-term storage. Accompanying this technology is the inherent responsibility to monitor these large-scale subsurface reservoirs for CO 2 leaks to ensure safety to local environments and inhabitants, as well as to alleviate global warming. Elevated CO 2 levels in soil are known to cause anoxic conditions in plant roots, thereby interfering with plant respiration and inducing a stress response that could possibly be remotely sensed using aerial imagery. Airborne remote sensing technology has the potential to monitor large land areas at a relatively small cost compared to alternative methods. In 2010, an aerial campaign was conducted during the height of the growing season to obtain an image time series that could be used to identify and characterize CO 2 stress in vegetation from a simulated CO 2 leak. An unsupervised classification was performed to classify CO 2 stressed vegetation as a result of the subsurface injection. Furthermore, a spectral index was derived to amplify the CO 2 stress signal and chart vegetation health trajectories for pixels affected by the CO 2 release. A theoretical framework was developed for analysis strategies that could be implemented to detect a CO 2 leak using aerial hyperspectral imagery with minimal a priori knowledge. Although aerial detection of CO 2 stressed vegetation was possible while no other physiological plant stressors were present, the spectral distinction between vegetation stress agents would have important implications for the appropriate timing that GCS monitoring using remote sensing data could commence. A greenhouse experiment was devised to compare the spectral responses of alfalfa plants to CO 2 and water stress in order to reveal whether CO 2 leak detection is possible when soil water availability is highly variable or during periods of drought. Spectral discernment of a CO 2 leak appears to be possible when soil water is spatially variable and during moderate drought conditions with remote sensing instruments that are sensitive to reflectance in the short wave infrared, where water absorption features related to leaf water content occur.




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