The paper “Spatio-Temporal Data Fusion for Very Large Remote Sensing Datasets” by Hai Nguyen, Matthias Katzfuss, Noel Cressie & Amy Braverman received the 2015 Wilcoxon Award for best practical application paper appearing the 2014 issues of Technometrics. The award was officially presented at the Fall Technical Conference, Oct. 8-9, 2015 in Houston, Texas. Technometrics is a journal of statistics for the physical, chemical, and engineering sciences, published by the American Society for Quality and the American Statistical Association. Distinguished Professor Noel Cressie is Director of NIASRA’s Centre for Environmental Informatics at UOW.
The paper describes a spatio-temporal data-fusion (STDF) methodology based on reduced-dimensional Kalman smoothing. The STDF is able to combine the complementary Japan’s Greenhouse gases Observing SATellite (GOSAT) and NASA’s Atmospheric InfraRed Sounder (AIRS) datasets to optimally estimate lower-atmospheric CO2 mole fraction over the whole globe. Further, it is designed for massive remote sensing datasets and accounts for differences in instrument footprint, measurement-error characteristics, and data coverages.