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large remote sensing datasets (e.g., Landsat, Sentinel-2, MODIS) and spatial datasets (e.g., FACTs, FTEM, field data) both locally with R/Python and via Google Earth Engine for wild-treatment outcome
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control) due to multiple interacting disturbances such as wildfires, drought, and insect outbreaks. The researcher will apply and adapt a spatially explicit multi-hazard risk assessment framework developed
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to achieve the following objectives: 1. Characterize 3-D Urban Structure and Change: Utilize data from multiple remote-sensing platforms and deep learning algorithms to generate high-resolution maps of 3-D
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