Averaging Atmospheric Gas Concentration Data using Wasserstein Barycenters
This addresses the challenge of accurately locating emission sources for environmental monitoring, but it appears incremental as it builds on existing averaging methods with a new technique.
The authors tackled the problem of pinpointing greenhouse gas emission sources from hyperspectral satellite data by proposing Wasserstein barycenters with weather data to average concentration data, resulting in better concentration of mass around significant sources.
Hyperspectral satellite images report greenhouse gas concentrations worldwide on a daily basis. While taking simple averages of these images over time produces a rough estimate of relative emission rates, atmospheric transport means that simple averages fail to pinpoint the source of these emissions. We propose using Wasserstein barycenters coupled with weather data to average gas concentration data sets and better concentrate the mass around significant sources.