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Mapping abrupt thaw slumps in the Arctic using deep neural networks and remote sensing
Yili Yang Data Scientist
美国伍德威尔气候研究中心
2023.7.31 10:30-11:30
测绘馆206会议室

报告人:Yili Yang(Data Scientist)

时间:2023.7.31 10:30-11:30

地点:测绘馆206会议室


报告人简介

   Dr Yili Yang is a data scientist at the Woodwell Climate Research Center focusing on solving geoscientific challenges using state-of-the-art data science, especially deep learning and computer vision. He is currently leading a project for mapping retrogressive thaw slumps (RTS) in the Arctic using Maxar high-resolution imagery, the Arctic DEM and Sentinel-2. Dr. Yang received his PhD from University of Edinburgh, UK in 2021.


报告简介

        Arctic terrestrial permafrost stores a great amount of carbon and is undergoing rapid change due to climate warming. Permafrost thaw can result in the rapid decomposition of soil carbon, releasing greenhouse gasses into the atmosphere. But the current Earth system models that include permafrost carbon only represent ‘gradual thaw’, so the impact of abrupt thaw is neglected. One fundamental limitation for us to understand the importance of abrupt thaw on Arctic landscapes is the lack of geospatial products describing their distribution and changes over time. We made the first step by developing a method to map abrupt thaw features using deep learning and satellite imagery.