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Erratum: Ramses A.M. et al. Vegetation Characterization through the Use of Precipitation-Affected SAR Signals. Remote Sens. 2018 10 1647., , , , и . Remote. Sens., 10 (11): 1854 (2018)Deep Neural Networks for Mapping Integrated Crop-Livestock Systems Using Planetscope Time Series., , , , , , , , , и . IGARSS, стр. 4224-4227. IEEE, (2021)Nitrogen variability assessment of pasture fields under an integrated crop-livestock system using UAV, PlanetScope, and Sentinel-2 data., , , , , , , и . Comput. Electron. Agric., (2022)Soil Erosion Satellite-Based Estimation in Cropland for Soil Conservation., , , , , , , , , и 3 other автор(ы). Remote. Sens., 15 (1): 20 (января 2023)Software AgDataBox-Map to precision agriculture management., , , , , , , , , и . SoftwareX, (2019)AgDataBox API - Integration of data and software in precision agriculture., , , , , , и . SoftwareX, (2019)Mapping Integrated Crop-Livestock Systems Using Fused Sentinel-2 and PlanetScope Time Series and Deep Learning., , , , , , , , , и 2 other автор(ы). Remote. Sens., 16 (8): 1421 (апреля 2024)Computational routines for the automatic selection of the best parameters used by interpolation methods to create thematic maps., , , , , и . Comput. Electron. Agric., (2019)Web applications for spatial analyses and thematic map generation., , , , , , и . Comput. Electron. Agric., (2020)Vegetation Characterization through the Use of Precipitation-Affected SAR Signals., , , , и . Remote. Sens., 10 (10): 1647 (2018)