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Active HORIZON European Commission

Climate-smart reforestation through the lens of remote sensing and microclimate sensors


Funder European Commission
Recipient Organization Technische Universitaet Muenchen
Country Germany
Start Date Sep 01, 2025
End Date Aug 31, 2027
Duration 729 days
Number of Grantees 5
Roles Associated Partner; Coordinator
Data Source European Commission
Grant ID 101151316
Grant Description

To address the escalating threat of climate change, there is an urgent need to develop smart strategies that bolster climate resilience.

Within the context of climate change mitigation and adaptation policies, reforestation plans stand out as one of the most crucial natural-based solutions.

However, the multifaceted role of forests as both warming and cooling agents presents a complicated challenge that remains a topic of ongoing debate.

By employing cutting-edge machine learning algorithms, advanced remote sensing technologies, and comprehensive ground-based empirical assessments this proposal, titled ""EcoClimate Navigator"", aims to uncover how smart reforestation plans can contribute to mitigating local climate change.

This project aims not only to enrich existing policy discussions around the topic of reforestation but also to add detailed and novel knowledge beyond what is already known on the role of forests in climate regulations at a global scale.

In addition to the expected outstanding outputs of this project, the Marie Sklodowska-Curie Action program will set the Experienced Researcher (EI), Sara Alibakhshi, on the right track to build her academic career and eventually become one of the future leaders in the field.

This program provides the EI with an excellent opportunity to conduct novel research along with new collaborations within the hosting organization and its partners, which is in line with the objectives of the Horizon Europe Framework Programme.

All Grantees

Crowther Lab Eth Zurich; Helsingin Yliopisto; Technische Universitaet Muenchen; Universidade de Evora; Universitaet Bern

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