Focus Area
Uncertainty Quantification for Remote Sensing Retrievals
We develop methods for quantifying uncertainties in retrieved estimates of geophysical quantities of interest (QoI's) produced by remote sensing observing systems. Each application is different, and we use foundational principles of Uncertainty Quantification to craft appropriate solutions for each situation. Sometimes we apply existing tools and techniques with proper modifications. In other cases, we research, develop, and implement new methodologies to address problems for which there are no existing methods. For the latter, our outside university partners collaborate with us closely on long-term research, often motivating Ph.D. dissertations for graduate students.
This work is in support of the following missions:
Related Publications
Braverman, A., Hobbs, J., Teixeira, J., and Gunson, M. (2021). “Post hoc uncertainty quantification for remote sensing observing systems,” SIAM/ASA Journal on Uncertainty Quantification, 9(3), pp. 1064–1093. Document (link to DOI) (CL 21-0606).
Hobbs, J., Braverman, A., Cressie, N., Granat, R., and Gunson, M. (2017). “Simulation-based uncertainty quantification for estimating atmospheric CO₂ from satellite data,” SIAM/ASA Journal on Uncertainty Quantification, 5(1), pp. 956–985. Document (link to DOI) (CL 17-2675).