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Detection of Flavescence dorée Grapevine Disease Using Unmanned Aerial Vehicle (UAV) Multispectral Imagery.

, , , , , , , and . Remote Sensing, 9 (4): 308 (2017)

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Imaging the World During Dry and Wet Seasons, Global Satellite Image Mosaics at Meter-Scale Resolution., , , , , , , and . IGARSS, page 2606-2609. IEEE, (2023)Detection of Flavescence dorée Grapevine Disease Using Unmanned Aerial Vehicle (UAV) Multispectral Imagery., , , , , , , and . Remote Sensing, 9 (4): 308 (2017)A comparative analysis of a fixed thresholding vs. a classification tree approach for operational burn scar detection and mapping., , , , and . Int. J. Appl. Earth Obs. Geoinformation, 11 (5): 299-316 (2009)Sensing Tropical Forest Phenology and Productivity from the Field to the Satellite., , , , , and . IGARSS, page 716-719. IEEE, (2021)On the Potentiality of UAV Multispectral Imagery to Detect Flavescence dorée and Grapevine Trunk Diseases., , , , , , , and . Remote Sensing, 11 (1): 23 (2019)Validation of a Forage Production Index (FPI) Derived from MODIS fCover Time-Series Using High-Resolution Satellite Imagery: Methodology, Results and Opportunities., , , , , and . Remote Sensing, 7 (9): 11525-11550 (2015)Airborne Lidar Sampling Pivotal for Accurate Regional AGB Predictions from Multispectral Images in Forest-Savanna Landscapes., , , , , and . Remote. Sens., 12 (10): 1637 (2020)