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D5.1 Environmental metrics methodology for ML-system

Authors: Nikolaos Tziolas, Nikolaos Tsakiridis;

D5.1 Environmental metrics methodology for ML-system

Abstract

The current report provides a set of recommendations for solid and measurable indicators with a focus on addressing environment and climate priorities within the framework of Common Agricultural Policy (CAP) implementation. In this context, DIONE generalizes and integrates the concept of Essential Variables (EVs) and Goal Based approach (GBA) across the main environmental objectives of the modernized new CAP (2021-2027). The work is driven by the need to support substantial monitoring and reporting by combining data primarily from satellites and novel aerial and in-situ solutions in the fields of land, soil, crop, water, air quality and climate change, and putting forward robust methodologies and well-defined workflows for linking the monitoring of EVs to key agricultural indicators. This is done by weighing in the readiness and maturity of existing agri-environmental indicators and monitoring methodologies, laying out EO-driven approaches for up-to-date and valid monitoring and paving the ground for a machine learning inferencing system. The report considered the implementation of CAP and other related environmental policies (e.g. SDGs), the outcomes and future perspectives of key research papers and relevant projects. Within the framework of ���D5.1 Environmental metrics methodology for ML-system��� DIONE brought together an interdisciplinary team of highly-performing scientists (agronomists, meteorologists, software engineers, EO experts), to jointly study the challenges to provide a comprehensive approach for environmental assessment of CAP.

Keywords

CAP, CAP environmental objectives, environmental monitoring, Copernicus, GEOSS, In-situ component, environment metrics, environment indicators

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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