Data Fusion and Spatial Inference for Remote Sensing
Building 3 Auditorium
(Coffee and cookies at 10:30 AM)
April 1, 2015
Remote sensing data are inherently spatial, and a substantial portion of their value for scientific analyses derives from the information they can provide about spatially dependent physical processes. However, no instrument observes everywhere all the time, and even where they do observe, their data have gaps and errors ...
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