Development of innovative fusion strategies and methods to improve vegetation characterization from multi-sensor remotely sensed data

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The long term goal of this proposed research program is to develop innovative integration strategies and fusion methods for the scientific advancement related to the accurate characterization of vegetation canopies from remotely sensed data. It is motivated and driven by technological developments in remote sensing and the demand for advancing science and innovation in vegetation characterization. Rapidly developed remote sensing technologies are making earth observation data widely available in unprecedented volume and detail; and meanwhile recent years have witnessed an increased demand for accurate determination of a growing number of attributes of vegetation canopies using remote sensing for sustainable management of forest resources, environment protection, and precision agriculture. The critical question we currently face is how to effectively utilize these data and intelligently integrate them together to improve vegetation characterization, such as the determination of vegetation types and conditions.