DeReEco: Deep Learning and Remote Sensing for Unlocking Global Ecosystem Resource Dynamics

DeReEco will combine remote sensing and artificial intelligence technologies to monitor, predict, and simulate changes in ecosystem properties – such as human settlement structures, agricultural use, tree and forest cover, water bodies, and carbon stocks – at a global scale. 

Based on newest remote sensing imagery, novel machine learning models will be developed to understand the complex relationships between temporal dynamics in geospatial datasets. The knowledge gained  on status, dynamics, and drivers of ecosystem changes will be pivotal in land degradation assessment (e.g.,  deforestation), in mitigating poverty (e.g., food security, agroforestry, wood products), and in managing climate change (e.g., carbon sequestration).






Name Title Phone E-mail
Ankit Kariryaa Postdoc   E-mail
Christian Igel Professor +4535335674 E-mail
Christin Abel Postdoc +4535332467 E-mail
Fabian Cristian Gieseke Associate Professor   E-mail
Gyula Mate Kovács PhD Fellow +4591922293 E-mail
Martin Stefan Brandt Associate Professor +4544164965 E-mail
Rasmus Fensholt Professor +4535322526 E-mail
Stefan Oehmcke Postdoc   E-mail
Stéphanie Marie Anne F Horion Associate Professor +4535325878 E-mail
Xiaoye Tong Postdoc +4535331239 E-mail