DURATION: 01.06.2021 to 31.05.2024
BUDGET: 150,000.00€/ 4,999,466.25€
FUNDING: H2020 Integrated GEOSS climate applications to support adaptation and mitigation measures of the Paris Agreement, RIA.
ABOUT EIFFEL
EIFFEL: Revealing the role of GEOSS as the default digital portal for Building Climate Change Adaptation & Mitigation Applications is a three year H2020 Research & Innovation Action project funded by topic Integrated GEOSS climate applications to support adaptation and mitigation measures of the Paris Agreement.
EIFFEL will offer the EO-based community the ground-breaking capacity of exploiting existing GEOSS and external datasets, with minimal new data collection activities. Added-value services interoperable with GEOSS will be designed, using cognitive search and metadata augmentation tools based on Artificial Intelligence (AI), including Natural Language Processing.
These tools will leverage advanced cognitive features to extract meaningful information from and enrich GEOSS metadata. Moreover, novel methods (super resolution, data fusion) for augmenting the spatiotemporal resolution of explored EO data will be proposed, in order to address the needs of the diverse EIFFEL CC adaptation and mitigation applications.
The latter will cover:
- a set of five different GEO Societal Benefit Areas (SBAs), namely in Water and Land Use Management, Sustainable Agriculture, Transport Management, Sustainable Urban Development and Disaster Resilience domains;
- various EU geographical and climatic regions, at local, regional, national, cross-border and pan-European scales. Further, the value of using explainable AI techniques for improving the credibility and comprehensiveness of such CC applications, so that they can offer actionable insights to the decision makers, will be showcased.
EIFFEL will foster the co-design of CC adaptation policies and mitigation strategies and monitor CC effects in the respective regions. The project, in line with EuroGEO’s emphasis on early engagement with stakeholders and their participation in the application design, has ensured that they are active consortium members. EIFFEL complies with the framework of results-Oriented GEOSS, to improve the delivery of applications tailored to decision making centres and will actively participate in the GEO Work Programme post-2019. Last, it provides tangible proof of the value of GEOSS data for creating CC applications and encourages projects and initiatives to offer their data through the portal.
OUR ROLE IN THE PROJECT
Key activity of UWMH in the EIFFEL project concerns the development of a suite of stochastic methods for the augmentation of the temporal resolution and quality of CC-related datasets. In particular, UWMH will design and develop theoretically justified methods and tools based on statistical and probabilistic notions such as those of, time series analysis, stochastic processes, and copulas to address three key challenges of CC-related datasets:
- lower-scale extrapolation (e.g., temporal downscaling),
- infilling of time series missing values, and
- generation of statistically consistent stochastic realizations.
The solutions delivered within this task will build upon the concept of Nataf’s joint distribution, a notion closely related to copulas, that has been recently and successfully used to address problems related to the stochastic simulation of non-Gaussian random variables, processes and fields.
The power and utility of the tools will be demonstrated through proof-of-concept applications in several cases, while the final output will be a general-purpose and easy-to-use, validated, toolbox for engineers and researchers working with time series data (e.g., meteorological ones) – substantially simplifying laborious tasks related to data (pre-) processing.
