SOURCE-LINKED INTELLIGENCE

Monitoring Functional Trait Dynamics of Forest Ecosystems under Climate Extremes Using Multi-model Remote Sensing

CORDIS · observation · Publication date unknown

the first high-temporal-resolution hyperspectral-estimated trait dataset and analysis for European forests. I will integrate recent hyperspectral images with long-term multispectral time series using machine learning approaches. This will generate a novel biweekly, high-resolution trait cube (2013–2026) across diverse European forest sites, representing diverse forest ecosystems. This state-of-the-art product will enable consistent monitoring of forest responses to recent climate extremes, capturing direct impacts, legacy responses, and indirect climate disturbances such as insect outbreaks. The objectives are: (i) to generate trait data cubes with a transferable fusion framework, (ii) to quantify trait dynamics and assess forest resistance and recovery under climate extremes and disturbances, beyond multispectral indices, and (iii) to explore the integration of trait-based ecosystem modelling. The fellowship will foster research independence through training at the interface of hyperspectral remote sensing, trait-based ecology, and ecosystem modelling. EcoSpectra will maximise the a

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recordType

award

status

SIGNED

region

EU

value

226420.56

unit

EUR