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Evaluation of RGB, Color-Infrared and Multispectral Images Acquired from Unmanned Aerial Systems for the Estimation of Nitrogen Accumulation in Rice.

, , , , , , , and . Remote Sensing, 10 (6): 824 (2018)

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DiNoDB: an Interactive-speed Query Engine for Ad-hoc Queries on Temporary Data., , , , , and . CoRR, (2016)Analysis of common canopy vegetation indices for indicating leaf nitrogen accumulations in wheat and rice., , , , and . Int. J. Applied Earth Observation and Geoinformation, 10 (1): 1-10 (2008)Predicting Rice Grain Yield Based on Dynamic Changes in Vegetation Indexes during Early to Mid-Growth Stages., , , , , , , , and . Remote Sensing, 11 (4): 387 (2019)Evaluation of Three Techniques for Correcting the Spatial Scaling Bias of Leaf Area Index., , , , , , and . Remote Sensing, 10 (2): 221 (2018)Evaluation of One-Class Support Vector Classification for Mapping the Paddy Rice Planting Area in Jiangsu Province of China from Landsat 8 OLI Imagery., , , , , , , , , and 1 other author(s). Remote Sensing, 10 (4): 546 (2018)Spectroscopic Estimation of Biomass in Canopy Components of Paddy Rice Using Dry Matter and Chlorophyll Indices., , , , , , , , and . Remote Sensing, 9 (4): 319 (2017)Comparative analysis of vegetation indices, non-parametric and physical retrieval methods for monitoring nitrogen in wheat using UAV-based multispectral imagery., , , , , , and . IGARSS, page 7362-7365. IEEE, (2016)Wavelet-based PROSPECT inversion for retrieving leaf mass per area (LMA) and equivalent water thickness (EWT) from leaf reflectance., , , , , , and . IGARSS, page 6910-6913. IEEE, (2016)Determination of optimal hyperspectral variables to monitor wheat biomass., , , , , , , and . IGARSS, page 3168-3169. IEEE, (2016)Evaluation of Landsat 8 time series image stacks for predicitng yield and yield components of winter wheat., , , , , and . IGARSS, page 6300-6303. IEEE, (2016)