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Retrieval of aboveground crop nitrogen content with a hybrid machine learning method.

, , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2020)

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Model-Based Optimization of Spectral Sampling for the Retrieval of Crop Variables with the PROSAIL Model., , , , , and . Remote. Sens., 10 (12): 2063 (2018)Assessing Non-Photosynthetic Cropland Biomass from Spaceborne Hyperspectral Imagery., , , , , , , , , and 1 other author(s). Remote. Sens., 13 (22): 4711 (2021)Top-of-Atmosphere Retrieval of Multiple Crop Traits Using Variational Heteroscedastic Gaussian Processes within a Hybrid Workflow., , , , , and . Remote. Sens., 13 (8): 1589 (2021)Prototyping Vegetation Traits Models in the Context of the Hyperspectral Chime Mission Preparation., , , , , , , , , and 8 other author(s). IGARSS, page 7678-7681. IEEE, (2021)Retrieval of Biophysical Crop Variables from Multi-Angular Canopy Spectroscopy., , , , and . Remote. Sens., 9 (7): 726 (2017)Hyperspectral Retrieval of Canopy Water Content Through Inversion of the Beer-Lambert Law., , , , and . IGARSS, page 3805-3808. IEEE, (2018)Developing a Sandbox Environment for Prosail, Suitable for Education and Research., , , , and . IGARSS, page 783-786. IEEE, (2018)RTM-based dynamic absorption integrals for the retrieval of biochemical vegetation traits., , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2020)Retrieval of aboveground crop nitrogen content with a hybrid machine learning method., , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2020)Towards Quantifying Non-Photosynthetic Vegetation for Agriculture Using Spaceborne Imaging Spectroscopy., , , , , , , and . IGARSS, page 5822-5825. IEEE, (2021)