Aufgabengebiet

I am currently working in a multidisciplinary PhD project focused on developing and applying Artificial Intelligence algorithms, within the remote sensing field.

My primary goal is to develop a data-driven method that utilizes both eddy covariance and satellite data, leveraging custom-made AI algorithms to accurately quantify the carbon sink on a regional scale within the Alps ecosystem.

Furthermore, I am actively involved in the development of AI-based techniques for monitoring vegetation stress levels. This involves analyzing multispectral and hyperspectral images acquired from both satellite and proximal sensing observations, to retrieve structural, functional, and biophysical parameters typical of plants, including fluorescence and fluorescence quantum yield.


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