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| Author | Title | Subject | Date | Publication Type | ||
|---|---|---|---|---|---|---|
| 1 |
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Cate, Nolan Randolph | A fully convolutional deep learning approach for using C-Band satellite radar imagery for forest biomass estimation | Geography; Computer science; Biomass; Deep learning; Forestry; Machine learning; Neural networks; SAR | 2019 | thesis |
| 2 |
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Smith, Constance Taylor | Evaluating the hydrological impact of removing woody biomass for biofuel production through unsaturated zone modeling | Biomass; Hydrological; Modeling; UNSAT-H; Unsaturated; Zone; Hydrologic sciences; Environmental engineering | 2017 | thesis |
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