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SAR and Optical Data Applied to Early-Season Mapping of Integrated Crop-Livestock Systems Using Deep and Machine Learning Algorithms.

, , , , , , , , и . Remote. Sens., 15 (4): 1130 (февраля 2023)

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Aline Dantas Araújo

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SAR and Optical Data Applied to Early-Season Mapping of Integrated Crop-Livestock Systems Using Deep and Machine Learning Algorithms., , , , , , , , и . Remote. Sens., 15 (4): 1130 (февраля 2023)Monitoring Pasture Aboveground Biomass and Canopy Height in an Integrated Crop-Livestock System Using Textural Information from PlanetScope Imagery., , , , , , , , , и . Remote. Sens., 12 (16): 2534 (2020)Comparison of Pasture Areas Over Brazil Biomes Using Global And National Land Cover Maps., , , , , , , , и . IGARSS, стр. 5988-5991. IEEE, (2019)Classification of Crops, Pastures, and Tree Plantations along the Season with Multi-Sensor Image Time Series in a Subtropical Agricultural Region., , , , , , , и . Remote. Sens., 11 (3): 334 (2019)Deep Neural Networks for Mapping Integrated Crop-Livestock Systems Using Planetscope Time Series., , , , , , , , , и . IGARSS, стр. 4224-4227. IEEE, (2021)Estimating pasture aboveground biomass under an integrated crop-livestock system based on spectral and texture measures derived from UAV images., , , , , и . Comput. Electron. Agric., (2022)Imputation of Missing Parts in UAV Orthomosaics Using PlanetScope and Sentinel-2 Data: A Case Study in a Grass-Dominated Area., , , , , , , , , и . ISPRS Int. J. Geo Inf., 12 (2): 41 (2023)Choosing pasture maps: An assessment of pasture land classification definitions and a case study of Brazil., , , , , , , , , и . Int. J. Appl. Earth Obs. Geoinformation, (2020)Nitrogen variability assessment of pasture fields under an integrated crop-livestock system using UAV, PlanetScope, and Sentinel-2 data., , , , , , , и . Comput. Electron. Agric., (2022)Evaluation of Time Series Gap-Filling of Venµs Satellite for Land Use Classification., , , , , и . IGARSS, стр. 4244-4247. IEEE, (2021)