Lisbon, Portugal, 23-24 January 2025

WG3 meeting Modelling vegetation traits and fluxes from optical remote-sensing data in croplands and forests

presentations on research that:

derives vegetation satellite products (LAI, leaf chlorophyll, FaPAR, GPP etc) from optical data (hyperspectral, multispectral, fluorescence), or

– validates existing satellite, airborne and UAV vegetation products using ground data.

WG3 Meeting. 23^rd – 24^th January, University of Lisbon, Portugal.

Theme: Modelling vegetation traits and fluxes from optical data in croplands and forests

*An aim of the meeting is that the presentations will feed into Obj 3.1 “To develop a validation strategy for priority vegetation products from near-term (upcoming) hyperspectral satellite missions (CHIME, ENMAP; SHALOM, SBG, FLEX) using ground based or airborne data.”

20 minute slots – 10 mins for presentations, 10 minutes for questions and handover.

Thurs 23^rd January
8.30 – 9.00		Coffee and registration
9.00 – 9.10	Holly Croft / Kadmiel Maseyk	Opening remarks
9.10 – 9.30	Sheng Wang	Quantifying Gross Primary Productivity and Evapotranspiration Across Europe Using Radiative Transfer Process-Guided Machine Learning
9.30 – 9.50	Zaib un nisa	Optimizing Cereal Crop Stress Assessment: Application of Machine Learning and Advanced Earth Observation Data for Multi-Stressor Analysis
9.50 – 10.10	Thang Quang Nguyen
10.10 – 10.30	Lorenz Haenchen	Measuring SIF (and more) at the FAIR site above the canopy
10.30 – 11.00		Coffee
11.00 – 11.20	Dessislava Ganeva	Evaluation of Copernicus HR-VPP product for crop phenology monitoring
11.20 – 11.40	Jessey Kwame Dickson	Improving satellite-based actual evapotranspiration estimations using data from local weather stations
11.40 – 12.00	Sélène Ledain	Comparison of LAI predictions on fields with developed models and existing global LAI models
12.00-12.20	Pablo Reyes-Muñoz	Leveraging Sentinel data and Gaussian process regression to unveil global patterns in terrestrial carbon fluxes.
12.20 – 2.30		Lunch
2.30 – 2.50	Viktor Ixion Mészáros	Implementation of Python Software for Estimating Vegetation Properties from Hyperspectral Satellite Data in the Prospect of CHIME
2.50 – 3.10	Shari Van Wittenberghe??	Unraveling the photosynthetic energy balance: spectral unmixing of multiple pigment fAPAR products from imaging spectroscopy
3.10 – 3.30	Lucas Casuccio	Training machine learning algorithm on in-silico multispectral imagery from 3D radiative transfer for retrieval of maize leaf chlorophyll content
3.30 – 3.50	Songyan Zhu	Unified FLUXes (UFLUX)v2 hyprid GPP upscaling overview
3.50 – 4.10		Coffee
4.10 – 4.30	Jorge Marques da Silva	Influence of epidermal trichomes on the optical properties of Quercus rotundifolia leaves: Consequences for satellite-derived vegetation indices
4.30 – 4.50	Maria Santos?
4.50 – 5.10	MaPi?
5.10-6.30?	Observatory tour
7.15	Dinner

Friday 24^th January
9.00 – 9.25	Satellite Mission Validation Strategy Objective 3.1. To develop a validation strategy for priority vegetation products from near-term (upcoming) hyperspectral satellite missions (CHIME, ENMAP; SHALOM, SBG, FLEX) using ground based or airborne data. Task 3.2. STSMs to investigate validation strategies of hyperspectral satellite mission products. These STMs will take place during GP2 and 3.
10.15 – 10.40	Coffee
10.40 – 12.15	Training school Task 3.1. Training School on the use of Google Earth Engine and other cloud-based EOS data and processing web platforms. The Training School will take place during GP2. Objective 3.2. To foster the use of big data and cloud computing for data fusion, time-series forecasting, and processing of spatiotemporally continuous vegetation products.
12.15 – 1.45	Lunch