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Identification of Cotton Root Rot by Multifeature Selection from Sentinel-2 Images Using Random Forest.

, , , , , and . Remote. Sens., 12 (21): 3504 (2020)

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Using Airborne and Satellite Imagery to Distinguish and Map Black Mangrove Along the South Texas Gulf Coast., , , and . IGARSS (1), page 472-475. IEEE, (2008)Unsupervised linear unmixing of hyperspectral image for crop yield estimation., , and . IGARSS, page 185-188. IEEE, (2010)GIS-based volunteer cotton habitat prediction and plant-level detection with UAV remote sensing., , , , , , and . Comput. Electron. Agric., (2022)Change detection of cotton root rot infection over 10-year intervals using airborne multispectral imagery., , , , and . Comput. Electron. Agric., (2016)Evaluation of Sentinel-2A Satellite Imagery for Mapping Cotton Root Rot., , , , , , and . Remote. Sens., 9 (9): 906 (2017)Evaluation of Orthomosics and Digital Surface Models Derived from Aerial Imagery for Crop Type Mapping., , , , , , , and . Remote. Sens., 9 (3): 239 (2017)Editorial for Special Issue: "Recent Progress in UAV-AI Remote Sensing"., , , and . Remote. Sens., 15 (18): 4382 (September 2023)Applying linear spectral unmixing to airborne hyperspectral imagery for mapping crop yield variability., , and . WHISPERS, page 1-4. IEEE, (2009)Crop Yield Estimation Based on Unsupervised Linear Unmixing of Multidate Hyperspectral Imagery., , , and . IEEE Trans. Geosci. Remote. Sens., 51 (1): 162-173 (2013)Integrating Growth and Environmental Parameters to Discriminate Powdery Mildew and Aphid of Winter Wheat Using Bi-Temporal Landsat-8 Imagery., , , , , , , , , and 1 other author(s). Remote. Sens., 11 (7): 846 (2019)