SUP Foundational Integrated Experiments (SUPFIX)

ESA CfP: /5-50124/25/I-KE-cl

MELA-SUPFIX Project

Multisource Earth observation integration for an improved assessment of Land processes

Project Overview

The MELA-SUPFIX project focuses on the development of a conceptual model and its application with real data for the generation of new Evapotranspiration (ET), Water Use Efficiency (WUE), and Nitrogen Use Efficiency (NUE) products.

The project will develop and validate a suite of novel retrieval algorithms and innovative prototype products for ET, WUE, and NUE, based on the combined capabilities of the forthcoming satellite missions:

These products will be configured to match Sentinel-2/CHIME/LSTM/FLEX/ROSE-L spatial resolutions, enabling improved monitoring of land processes through integrated Earth observation.

Project Objectives

Conceptual Model Development

Develop a comprehensive conceptual model for integrating multisource Earth observation data to assess land processes.

Algorithm Development

Create and validate novel retrieval algorithms for ET, WUE, and NUE products using combined mission capabilities.

Data Integration

Harmonize existing datasets for calibration/validation and develop workflows for future ET, WUE, and NUE monitoring.

Experimental Campaign

Conduct ground and airborne measurements campaigns in 2026 for validation of developed products and methods.

Target Missions

The project specifically targets the following Earth observation missions (click for more information):

Specific Technical Objectives

  1. Harmonization of existing data for calibration/validation and identification of gaps in the historical dataset with reference to the selected target area.
  2. Design of a new field/airborne campaign and collect new data in 2026 to complement the pre-existing dataset with a special attention to the improvement of the representation of the daily course of key parameters.
  3. Develop, test and validate a RT model to simulate reflectances, temperatures, and fluorescences in Sentinel2/CHIME/LSTM/FLEX configuration (L2 products).
  4. Estimate ET using traditional models based on past data and the new campaign (benchmark) at LSTM resolution.
  5. Development (training and validation) of Bayesian and Machine Learning models, as well as physical models, for the estimation of ET, WUE, and NUE.
  6. Developing a 3D simulation for indirect validation for the LSTM/CHIME/FLEX missions.
  7. Recommendations for synergistic EO applications.
  8. Generate a Reference Open Dataset for the i) storage of historical and new data, ii) run the models developed along the project in operational mode with real data to generate ET, WUE and NUE outputs.
Reference Open Dataset (ROD) Conceptual Design
Reference Open Dataset (ROD) Conceptual Design
Sentinel 2 false color images of the Grosseto plain in May (left) and July (right) 2024
Sentinel 2 false color images of the Grosseto plain in May (left) and July (right) 2024. Red color highlights the presence of vegetation: in the month of May (wet period) winter-crops are at full canopy development while, in July (dry period), only irrigated summer-crops are visible.

Project Timeline

10/2025
KO Meeting
01/2026
SR/CIP Submission
05/2026
IOP 1 Campaign
07/2026
IOP 2 Campaign
10/2026
ATBD Delivery
09/2027
SAR Submission
04/2028
Final Meeting

Key Campaign Periods

Experimental Campaign 2026: Ground and airborne measurements including hyperspectral and fluorescence data collection (May-July 2026).

Grosseto Dataset: Pre-existing data from 2017-2025 will be utilized for model development and validation.

Work Packages

The MELA-SUPFIX project is organized into several work packages covering different aspects of the research and development process.

WP-120

Scientific Requirements

Definition and consolidation of scientific requirements for the project.

WP-210 to 240

Experimental Campaign

Logistics, ground measurements, airborne RS, and airborne fluxes activities.

WP-310 to 330

Reference Open Dataset

Conceptual design, generation, and harmonization of reference open database.

WP-410

SCOPE RT Model

Testing and validation of SCOPE RT model for land process monitoring.

WP-420

ET Estimation

Evapotranspiration estimation via SEBI-like approaches.

WP-430

Optimal Estimation

Development of methods for WUE, NUE and ET retrieval using optimal estimation.

WP-440

Machine Learning

Development of WUE, NUE and ET retrieval using Machine Learning techniques.

WP-450

Validation

Validation of proposed retrieval methods using ground and airborne measurements.

WP-460

Synthetic Validation

Synthetic validation using 3D models for algorithm testing.

WP-510

Workflow Pipeline

Development of workflow and pipeline for future ET, WUE and NUE monitoring.

WP-610 to 620

Outreach & Synergies

Promotion, outreach activities and collaboration synergies.

Project Partners

The MELA-SUPFIX project brings together leading research institutions and organizations:

Click on any partner logo to visit their official website

Key Deliverables

Science Requirements (SR)

This deliverable will report the detailed description of the science plan of the project, including:

Additional Deliverables

  • ATBD (Algorithm Theoretical Basis Document) - October 2026
  • SAR (Science Analysis Report) - September 2027
  • Scientific Roadmap - February 2028
  • Harmonized datasets for calibration and validation
  • MELA modelling tool with SIF integration strategies