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  • title: Aboveground Carbon Biomass Estimate with Physics-informed Deep Network
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            Aboveground Carbon Biomass Estimate with Physics-informed Deep Network
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            Aboveground Carbon Biomass Estimate with Physics-informed Deep Network

            Dec 2, 2022

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            JN

            Juan Nathaniel

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            The global carbon cycle is a key process to understand how our climate is changing. However, monitoring the dynamics is difficult because a high-resolution robust measurement of key state parameters including the aboveground carbon biomass (AGB) is required. We use deep neural network to generate a wall-to-wall map of AGB within the Continental USA (CONUS) with 30-meter spatial resolution for the year 2021. We combine radar and optical hyperspectral imagery, with a physical climate parameter of…

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            NeurIPS 2022

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