Remote sensing, or the science of capturing data of the earth from airplanes or satellites, enables regular monitoring of land, ocean, and atmosphere expanses, representing data that cannot be captured using any other means. A vast amount of information is generated by remote sensing platforms and there is an obvious need to analyze the data accurately and efficiently to improve throughput, reduce costs, and create new products. Whereas human operators can effectively interpret remotely sensed imagery, there is no known artificial algorithm able to perform such a task. Members of the VIP research team conduct remote sensing research to solve problems in denoising, disparate scene registration, multi-sensor fusion, region segmentation, and scene classification. The overall objective of the proposed research is to design more effective automated information extraction algorithms for interpreting remote sensing imagery. A key research area within the VIP lab is the automated classification of sea ice images derived from the synthetic aperture radar (SAR) sensor.