Large-scale monitoring of nature with deep learning

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  • Date
    10 January 2024
    Timeframe
    17:00 - 18:15 CET Geneva
    Duration
    75 minutes (includes 15 minute networking)
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    Modern deep learning in combination with satellite data offers great opportunities to protect nature at global scale. In this talk, I will present ongoing research to estimate snow depth, map crops at country-scale, and estimate vegetation parameters such as biomass or vegetation height. Traditional approaches usually have to be adapted for specific ecosystems and regions. It is therefore very difficult to carry out homogeneous, large-scale modeling with high spatial and temporal resolution and, at the same time, good accuracy. Data-driven approaches, especially modern deep learning methods, promise great potential here to achieve globally consistent, transparent assessments of our environment. 

    This live event includes a 15-minute networking event hosted on the AI for Good Neural Network. This is your opportunity to ask questions, interact with the panelists and participants and build connections with the AI for Good community.

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