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Monitoring Corn Nitrogen Concentration from Radar (C-SAR), Optical, and Sensor Satellite Data Fusion
Remote Sensing,
2023
DOI:10.3390/rs15030824
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A Globally Applicable Method for NDVI Estimation from Sentinel-1 SAR Backscatter Using a Deep Neural Network and the SEN12TP Dataset
PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science,
2023
DOI:10.1007/s41064-023-00238-y
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[3]
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Assimilation of Multisensor Optical and Multiorbital SAR Satellite Data in a Simplified Agrometeorological Model for Rapeseed Crops Monitoring
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
2022
DOI:10.1109/JSTARS.2021.3136289
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[4]
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Assimilation of Multisensor Optical and Multiorbital SAR Satellite Data in a Simplified Agrometeorological Model for Rapeseed Crops Monitoring
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
2022
DOI:10.1109/JSTARS.2021.3136289
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Evaluation of Multiorbital SAR and Multisensor Optical Data for Empirical Estimation of Rapeseed Biophysical Parameters
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
2021
DOI:10.1109/JSTARS.2021.3095537
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Estimation of Crop Water Deficit in Lower Bari Doab, Pakistan Using Reflection-Based Crop Coefficient
ISPRS International Journal of Geo-Information,
2020
DOI:10.3390/ijgi9030173
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Contribution of multispectral (optical and radar) satellite images to the classification of agricultural surfaces
International Journal of Applied Earth Observation and Geoinformation,
2020
DOI:10.1016/j.jag.2019.101972
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Temporal Evolution of Corn Mass Production Based on Agro-Meteorological Modelling Controlled by Satellite Optical and SAR Images
Remote Sensing,
2019
DOI:10.3390/rs11171978
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Estimation of Corn Yield by Assimilating SAR and Optical Time Series Into a Simplified Agro-Meteorological Model: From Diagnostic to Forecast
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
2018
DOI:10.1109/JSTARS.2018.2878502
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[10]
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Combining optical remote sensing data with in-situ measurements in order to estimate vegetation parameters on agricultural fields and corresponding uncertainties
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX,
2017
DOI:10.1117/12.2280409
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[11]
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Estimation of corn yield using multi-temporal optical and radar satellite data and artificial neural networks
International Journal of Applied Earth Observation and Geoinformation,
2017
DOI:10.1016/j.jag.2016.12.011
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