WG4 Uncertainty Analysis and Standardization

WG4 aims to develop coherent and standardized measurement protocols, guidelines and examples of the estimation and propagation of uncertainties for the different monitoring tools used in phenotyping, precision agriculture and land management. This work will be performed in collaboration with WGs 1-3, supporting them in the goal of providing products accompanied with uncertainty estimates to the final end-users (e.g., farmers, crop managers and stakeholders). This will be enabled by specific training sessions provided to members of WGs 1-3, best practice and guidelines on calibration and validation of monitoring tools, data quality and performance assessment of different measurements approaches, robust quantification of the uncertainty along a traceable processing chain, thus paving the way towards the operational computation of propagated uncertainties within processing chains.

Objectives

• O4.1. Evaluate the performance of different RS methodologies used within the network and to develop a common protocol to assess their accuracy and SI traceability.
• O4.2. Develop standardized and optimized best practice protocols for assessment of spectral and radiometric performance of advanced proximal and remote sensing monitoring tools used across the WGs to establish their traceability chain and thus enabling technological improvements in the fields crop breeding, phenotyping, and forest genetics for future EU climate resilience.
• O4.3. Develop practical examples for the quantification of uncertainty budgets associated with selected monitoring tools of the other WGs and to provide access to software implementations of these examples.

Tasks

• T4.1. Common workshop to establish the status quo of different monitoring approaches within the network, documenting the traceability chains of WG specific, selected case studies. – Case selection in Poznan, Poland, 8-10 May 2024 – Optimal and cost-effective UAV sensor synergies for trait-based field phenotyping and precision agriculture Workshop 1 organized by WG1+WG2. Case studies examples provided in https://github.com/pangeos-cost/uq-training
• T4.2. Training schools and STSMs with other WGs to train and support researchers in uncertainty analysis and propagation. Materials from training school in Romania: https://github.com/pangeos-cost/uq-training
• T4.3. Develop software for the applied propagation of uncertainties from sensors to products.

Deliverables

• D4.1. Publication documenting the status quo of traceability in the form of uncertainty tree diagrams for selected case studies: https://github.com/pangeos-cost/uq-training
• D4.2. Dissemination of training material focused on WG specific case studies: https://github.com/pangeos-cost/uq-training
• D4.3. Dissemination of software for the propagation of uncertainties for selected case studies.

Meetings GP3, 2026

• Participation in WG 1+2 Meeting Hackathon Paper, Mojstrana, Slovenia, 20-22 January 2026
• WG1+4 Meeting Field Day Two Deliverable Papers, Ben Guerir, Morocco, 5-6 February 2026.
• WG 2 Meeting CGM and EO Paper, Athens, Greece, 18-20 March 2026
• Participation to Training School  “Remote sensing methods on determining evapotranspiration”  13.04.2026-17.04.2026 in Nitra, Slovakia 
• WG4 Meeting – finalise GP3 deliverables, Varna, Bulgaria, 10-11 September 2026

Meetings GP2, 2025

• WG4 meeting on uncertainty propagation in ARTMO, Valencia, Spain, 27-31 January 2025
• Participation in Joint WG1-WG2 Field Day: Remote Sensing & Proximal Phenotyping in Action, Norwegian University of Life Sciences, Ås, Norway, 19-20 June 2025
• Participation in Hackathon of WG1 and WG2 on Improving crop growth models by the inclusion of remote sensing, Aarhus, Denmark, 28-29 August 2025

Meetings GP1, 2024

• 2024-03-01 (virtual) kick-off. Agenda
• 30 September-4 October 2024, Bucharest, Romania – Joint uncertainty analysis and protocol standardization assessment summer school on novel and operational hyperspectral data products: Training material in Jupyter Notebooks and presentations are available on GitHub https://github.com/pangeos-cost/uq-training

Leader