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Mapping Forest Canopy Structure With On-Demand Fusion Of Remotely Sensed Data, Gordon M. Green
Mapping Forest Canopy Structure With On-Demand Fusion Of Remotely Sensed Data, Gordon M. Green
Dissertations, Theses, and Capstone Projects
Current methods of mapping forest canopy structure often result in data products that are limited in resolution, coverage, or ease of access. On-demand processing introduces several new ways in which existing data products can be combined and re-purposed, mitigating some of these limitations. In this research, we investigate several methods of extending the spatial and temporal resolution, coverage, and accessibility of existing forest canopy datasets by processing them on demand. These methods include downscaling coarse-resolution canopy height data dynamically to estimate height at 30 m and 1 m resolution for any location within the contiguous United States. A related method …