CEI research

Statistical remote sensing

Remote sensing of geophysical variables almost always involves indirect measurements of energies in relevant bands of the electro-magnetic spectrum, taken by an instrument on board a satellite or some other flight vehicle. For any one measurement at a given location and time, inference on states of the atmosphere is carried out in the presence of uncertainty. 

Local flux inversion

Local flux inversion is concerned with locating and quantifying point sources and sinks in a small area of interest, generally on the order of a few thousand square metres or a few square kilometres. At these scales, simple atmospheric models can be used, and precise quantification of emissions can be done. (Image credit: Stephan Muller)

Regional flux inversion

Regional flux inversion is concerned with locating and quantifying sources and sinks at much larger scales (spanning whole countries, or a continent). This inversion setup is useful for validating a country's emission portfolio, for example, to ensure that it is complying with any emission targets in place. (Image credit: NASA)

Global flux inversion

Global flux inversion is concerned with locating and quantifying sources and sinks at the global scale. Inversion at this scale requires the use of global atmospheric transport models, as well as sophisticated computational machinery to deal with massive data sets. (Image credit: NASA) 

Space-based research in spectroscopy

Understanding the chemical composition of mineral and biological samples is vital for many practical applications, including the search for evidence of past life on Mars, environmental monitoring of coral health and water quality, and medical diagnostics of cancer and other diseases. (Image credit: NASA)

Conditional models

When using conditioning for model construction one only needs univariate covariance functions to yield valid multivariate models. The approach we develop has a vast array of applications since it features conditional dependencies on a potential causative process. The project on regional methane flux mapping given on the page, Regional flux inversion, is one such application.

Models on warped spaces

Complex multivariate spatial covariance models can be constructed by taking a very simple, valid, multivariate spatial covariance model, and then warping the spatial domain on which it is defined. We find that warping can easily induce properties such as nonstationarity and asymmetry.