PhD project aims to use deep learning/computer vision approaches to classify different forest disturbance types in remote-sensing data (fires, insects, storms). This is fundamental to quantify the carbon footprint associated with large scale disturbances and potential feedbacks with climate change. This position is funded by the ERC StG project ForExD “Forest vulnerability to compound extremes and disturbances in a changing climate”.
Find more in the ELLIS PhD Program: https://ellis.eu/news/ellis-phd-program-call-for-applications-2022
Deadline November 15 2022