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HARMONIA will provide a newsletter to inform stakeholders about developments related to the project. Sign up to stay in the loop!
Project Harmonia Presentation Video
HARMONIA leverages a wealth of existing Earth Observation (EO) Datasets and services ‒ including GEOSS, Copernicus and ESA data and services. This will be capitalised with ensemble modelling of socio-economic and in-situ data to deliver an Integrated Resilience Assessment Platform (IRAP). IRAP is a system that allows stakeholders to model a range of planning options against a number of CC scenarios.
The IRAP platform will address multi-hazard risk factors and help streamline the process of preparing for, and responding to, Climate Change-related hazards.
HARMONIA Publications
HARMONIA brochure
The HARMONIA brochure contains more detailed information and will be expanded with additional content as the project progresses. Stay tuned!
Download the 1st newsletter - February 2022
Download the 2nd newsletter - March 2023
HARMONIA Leaflet
The HARMONIA leaflet contains key information for stakeholders, including the objectives of the project and its added value. Share it among your network and help spread the word!
Download the leaflet
Deliverable 1.1: Data management plan & Data ethics report
The Data Management Plan aims to be the point of reference when managing data generated within the context of the project, to ensure an effective and sustainable exploitation of the results also beyond the project duration.
Download Deliverable 1.1
Deliverable 2.1: Stakeholders Engagement Plan
The deliverable 2.1 is a plan detailing the the methodology for achieving maximum engagement of relevant stakeholders of HARMONIA.
Download Deliverable 2.1
Deliverable 2.3: Requirements and availability on data acquisition, transformation & intelligence extraction
This document describes the outputs of HARMONIA Task 2.2 which is concerned with analysis of the data and processing models and algorithms that are needed to fulfil the HARMONIA applications.
Download Deliverable 2.3
Deliverable 3.5 Data Annotation Report
This document outlines the assessment and pre-processing of datasets to train Deep Learning models, aimed at deriving urban land cover information from Earth observation data in European pilot cities (Sofia, Milan, Athens, Brussels).
Download the Deliverable
