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Zhe Zhu
University of ConnecticutMeeting roles in:
Continuous disturbance induced forest loss accelerates forest edge expansion in the U.S.
Enhanced Forecasting Methods for Extreme Weather Events and Vulnerable Populations
Science and Applications Enabled by Remote Sensing Data Fusion, Time Series Analysis, and AI I Poster
Building California-tailored disturbance monitoring system using long-term and continuous Landsat data
Physics-Informed Machine Learning for Cloud Detection
Science and Applications Enabled by Remote Sensing Data Fusion, Time Series Analysis, and AI II Oral
Global Land Cover mapping and Estimation (GLanCE): Long-term Annual Datasets from Landsat-CCDC Across Five Continents
Mapping Caribbean Primary Forest Change Considering Disturbance History, Resilience, and 3D Structure
Satellite evidence for a shift from human-directed to wild disturbances in the US
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