Forest disturbance in a changing world

A new approach for scaling vegetation dynamics

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A novel approach for scaling vegetation dynamics based on deep learning was published recently in Methods in Ecology and Evolution. The modeling framework developed by Werner Rammer and Rupert Seidl allows a consistent scaling of local vegetation dynamics (with abundant data and high process understading) to much larger spatial extents (think: country to continental level). At the core, the model harnesses deep learning, which is an exciting new branch of machine learning that revolutionized many fields of computer science in the last years.

Written by Admin on Friday March 15, 2019

Sucessful research visit to the US

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PhD student Katharina Albrich visited Prof. Monica G. Turner and her team at the University of Wisconsin in Madison!

Written by katharina on Monday November 5, 2018


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The Austrian public television ORF invited Rupert Seidl to talk about the latest RESIN publication on “Aktuell in Österreich”

Written by rupert on Thursday April 26, 2018