Enze Zhang, PhD student
Enze’s research focuses on terminus variations of glaciers in Greenland, quantifying such variations in a high temporal resolution and understanding their controlling factors. Based on deep learning, he develops a method to extract the calving front automatically using multi-sensor remote sensing imagery (TerraSAR-X, Sentinel-1, Landsat). He also analyzes the controlling factors of the calving front variations by combining other data such as glacier velocity and bed elevation.
TerraSAR-X image over Jakobshaven Isbræ. The red line indicates the calving front position, delinated using a Deep Learning method.