Estimating and understanding crop yields with explainable deep learning in the Indian Wheat Belt

Deep learning and process understanding for data-driven Earth system science

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Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

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Methods for interpreting and understanding deep neural networks

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Satellite sun-induced chlorophyll fluorescence detects early response of winter wheat to heat stress in the Indian Indo-Gangetic Plains

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Machine learning methods for crop yield prediction and climate change impact assessment in agriculture

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Crop production losses associated with anthropogenic climate change for 1981-2010 compared with preindustrial levels

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Estimating global agricultural effects of geoengineering using volcanic eruptions

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Explanation in artificial intelligence: Insights from the social sciences

(2018) Tim Miller   ARTIFICIAL INTELLIGENCE

Using satellite data to identify the causes of and potential solutions for yield gaps in India’s Wheat Belt

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The shared and unique values of optical, fluorescence, thermal and microwave satellite data for estimating large-scale crop yields

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Google Earth Engine: Planetary-scale geospatial analysis for everyone

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Canopy near-infrared reflectance and terrestrial photosynthesis

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Deep learning

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Elucidating the impact of temperature variability and extremes on cereal croplands through remote sensing

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Recent patterns of crop yield growth and stagnation

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Extreme heat effects on wheat senescence in India

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Shifting boundaries: challenges for rust monitoring

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Climate Trends and Global Crop Production Since 1980

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