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Computational routines for the automatic selection of the best parameters used by interpolation methods to create thematic maps.

, , , , , and . Comput. Electron. Agric., (2019)

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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., , , , and . Remote. Sens., 10 (11): 1854 (2018)Deep Neural Networks for Mapping Integrated Crop-Livestock Systems Using Planetscope Time Series., , , , , , , , , and . IGARSS, page 4224-4227. IEEE, (2021)Nitrogen variability assessment of pasture fields under an integrated crop-livestock system using UAV, PlanetScope, and Sentinel-2 data., , , , , , , and . Comput. Electron. Agric., (2022)AgDataBox API - Integration of data and software in precision agriculture., , , , , , and . SoftwareX, (2019)Software AgDataBox-Map to precision agriculture management., , , , , , , , , and . SoftwareX, (2019)Soil Erosion Satellite-Based Estimation in Cropland for Soil Conservation., , , , , , , , , and 3 other author(s). Remote. Sens., 15 (1): 20 (January 2023)Computational routines for the automatic selection of the best parameters used by interpolation methods to create thematic maps., , , , , and . Comput. Electron. Agric., (2019)Vegetation Characterization through the Use of Precipitation-Affected SAR Signals., , , , and . Remote. Sens., 10 (10): 1647 (2018)Web applications for spatial analyses and thematic map generation., , , , , , and . Comput. Electron. Agric., (2020)SAR and Optical Data Applied to Early-Season Mapping of Integrated Crop-Livestock Systems Using Deep and Machine Learning Algorithms., , , , , , , , and . Remote. Sens., 15 (4): 1130 (February 2023)