Spatial Statistics for Satellite Remote Sensing Data

• Activity Number: 100
• Type: Invited
• Date/Time: Monday, August 4, 2014 : 8:30 AM to 10:20 AM
• Sponsor: International Indian Statistical Association
• Author(s): Noel Cressie*+
• Companies: NIASRA/University of Wollongong
• Keywords: Atmospheric CO2 ; Spatial statistical analysis ; Spatial statistical data fusion ; Visualization on the globe

Abstract

Remote sensing data from satellites are not direct measurements of a physical or chemical property. They are radiances detected by a spectrometer onboard a satellite. A retrieval for each sounding is obtained by solving a non-linear inverse problem. The resulting geophysical data are often sparse and incomplete with respect to the globe as a whole. Statistical methods of visualization and analysis are needed that are able to exploit spatial (and temporal) dependencies in the data. Such methods need to accommodate differing spatial variability and dependencies around the globe, they need to allow for change-of-support, and they need to yield computationally feasible statistical inferences for these environmental Big-Data. In this talk, I shall describe joint work with co-researchers on a grant from NASA's Earth Science Technology Office, that tackles these problems.