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PRAIRIE Webinar: Machine learning for climate change: Analysis of remote sensing data

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Machine learning for climate change: Analysis of remote sensing data

Abstract:

There is currently a wealth of openly-available data generated by remote sensing platforms (including satellite and aerial imagery). This data can be of use for tackling a variety of problems related to climate change in terms of mitigation, adaptation, conservation, disaster response, and planning. In this talk, I will give an overview of some of these problems along with the relevant data sources and models that can be used to help tackle them. I will also discuss two ongoing projects in my lab, one on the remote analysis of the power grid and another on surveying the impacts of beaver dams. Finally, I will discuss my somewhat unorthodox path to this research area (coming from a neuroscience background) and provide resources for getting into work on climate change

Proposé par

  • Intervenant externe
    I
    Grace Lindsay Assistant Professor of Psychology and Data Science @ NYU

  • Intervenant externe
    I
    Jean Ponce Ecole normale supérieure-PSL and New York University Prairie 3IA Institute Enhance Lab

Inria

Institut national de recherche en sciences et technologies du numérique