HEИндивидуална стипендия2026–2028

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

„Хоризонт Европа“ — Действия „Мария Склодовска-Кюри“

Период
2026-10-01 → 2028-09-30
Финансиране от ЕС
226 421 €
Участници
1
Схема
HORIZON-TMA-MSCA-PF-EF

Линиите свързват координатора с партньорите.

Накратко на български

Динамиката на растителните характеристики, като съдържанието на хлорофил и вода в европейските гори, се проследява чрез сателитни данни и машинно обучение. Това помага да се разбере как горите реагират и се възстановяват след екстремни горещини, суша или нападения от насекоми.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Цел на проекта

Europe is experiencing increasingly frequent climate extremes—heatwaves, droughts, and compound events—that threaten forest ecosystem stability. Current forest monitoring mainly relies on multispectral data, lacking spectral resolution to retrieve key plant traits and physiological stress. Spaceborne hyperspectral sensors (e.g., PRISMA, EnMAP) overcome this limitation by providing finer spectral information, improving the estimation of traits impacted by climate extremes, such as chlorophyll, carotenoids, potassium, and water content. However, their sparse temporal coverage hinders ecological change monitoring. EcoSpectra will fill this gap by producing 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 application of next-generation hyperspectral missions (e.g., ESA CHIME) in ecological research, advance understanding of how European forests respond to climate stress, and support EU forest and climate strategies.

Оригинален текст от CORDIS (на английски).

Участници

  • UNIVERSITE DE VERSAILLES SAINT-QUENTIN EN YVELINES · VERSAILLESКоординаторФранция

Връзки

Данни: CORDIS, © Европейски съюз