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Found 2 papers, 2 papers with code
Multi-modal learning for geospatial vegetation forecasting
Our study breaks new ground by introducing GreenEarthNet, the first dataset specifically designed for high-resolution vegetation forecasting, and Contextformer, a novel deep learning approach for predicting vegetation greenness from Sentinel 2 satellite images with fine resolution across Europe.
Learning to forecast vegetation greenness at fine resolution over Africa with ConvLSTMs
Forecasting the state of vegetation in response to climate and weather events is a major challenge.
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