ROBUST FINGERPRINTING METHOD FOR WEBTOON IDENTIFICATION IN LARGE-SCALE DATABASES



Extracting Agronomic Information from SMOS Vegetation Optical Depth in the US Corn Belt Using a Nonlinear Hierarchical Model

Remote sensing observations that vary in response to plant growth and senescence can be used to monitor crop development within and across growing seasons.Identifying when crops reach specific growth stages can improve harvest yield prediction and quantify climate change.Using the Level 2 vegetation optical depth (VOD) product from the European Spa

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