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Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data.

, , , , , , , и . Remote. Sens., 10 (9): 1346 (2018)

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Grégory Nain

Grégory Païs

Grégory Mallet

Grégory Smits

Grégory Batt

 

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Local adjustments of image spatial resolution to optimize large-area mapping in the era of big data., , и . Int. J. Appl. Earth Obs. Geoinformation, (2018)Defining the Spatial Resolution Requirements for Crop Identification Using Optical Remote Sensing, и . Remote Sensing, (2014)Testing the Contribution of Stress Factors to Improve Wheat and Maize Yield Estimations Derived from Remotely-Sensed Dry Matter Productivity., , , , и . Remote Sensing, 8 (3): 170 (2016)Mapping Carbon Stocks In Central And South America With Smap Vegetation Optical Depth., , , , , , и . IGARSS, стр. 5449-5452. IEEE, (2019)A Method to Determine the Appropriate Spatial Resolution Required for Monitoring Crop Growth in a given Agricultural Landscape., , и . IGARSS (3), стр. 562-565. IEEE, (2008)Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data., , , , , , , и . Remote. Sens., 10 (9): 1346 (2018)Estimating regional wheat yield from the shape of decreasing curves of green area index temporal profiles retrieved from MODIS data., , , , , и . Int. J. Appl. Earth Obs. Geoinformation, (2012)Impact of Categorical and Spatial Scale on Supervised Crop Classification using Remote Sensing, , , и . Photogrammetrie - Fernerkundung - Geoinformation, 2015 (1): 7-20 (2015)