Explore the words cloud of the DIONE project. It provides you a very rough idea of what is the project "DIONE" about.
The following table provides information about the project.
INSTITUTE OF COMMUNICATION AND COMPUTER SYSTEMS
|Coordinator Country||Greece [EL]|
|Total cost||2˙377˙125 €|
|EC max contribution||1˙999˙837 € (84%)|
1. H2020-EU.18.104.22.168. (Enabling European competitiveness, non-dependence and innovation of the European space sector)
2. H2020-EU.22.214.171.124. (Enabling exploitation of space data)
|Duration (year-month-day)||from 2020-01-01 to 2022-06-30|
Take a look of project's partnership.
|1||INSTITUTE OF COMMUNICATION AND COMPUTER SYSTEMS||EL (ATHINA)||coordinator||463˙875.00|
|2||DIABALKANIKO KENTRO PERIBALLONTOS||EL (LAGADAS THESSALONIKI)||participant||288˙750.00|
|3||CORE INNOVATION AND TECHNOLOGY OE||EL (CHALKIS)||participant||241˙937.00|
|4||GILAB DOO BEOGRAD-PALILULA||RS (BEOGRADE)||participant||224˙875.00|
|5||SINERGISE LABORATORIJ ZA GEOGRAFSKEINFORMACIJSKE SISTEME DOO||SI (LJUBLJANA)||participant||221˙900.00|
|6||NATIONAL PAYING AGENCY||LT (VILNIUS)||participant||218˙125.00|
|7||INOSENS DOO NOVI SAD||RS (NOVI SAD)||participant||191˙625.00|
|8||ORGANISMOS AGROTIKON PLIROMON||CY (STROVOLOS)||participant||148˙750.00|
DIONE proposes a close-to-market (TRL7) area-based direct payments monitoring toolbox that will address the forthcoming Modernised CAP regulation of using automated technologies to ensure more frequent, accurate and inexpensive compliance checks. In particular, DIONE will: (i) Capitalise on recent results of ESA’s SEN4CAP project that showcased the capability of Sentinel data to monitor the crop diversification rules. DIONE shall further integrate generated crop-type maps in a way directly exploitable by the paying agencies; (ii) Include in the analysis the so far neglected EFA types (fallow land of all sizes, buffer strips, hedges, trees), by making use of super-resolution technology that improves the 10-20m Sentinel resolution to an improved resolution range (5-10m). This is enabled through Machine-Learning (ML) based post-processing and data fusion of Copernicus DIAS-sourced data with targeted drone-obtained data. This aims to motivate the use of such EFAs over the –of ambiguous environmental impact- use of productive areas (nitrogen-fixing crops and catch crops). (iii) Complement the use of EO data with a system of reliable, ground-based geo-tagged photos, captured by the farmers that exploits (a) advances that allow for improved positional accuracy, (ii) low-footprint encryption techniques for improved data security and reliability and (iii) image detecting manipulation techniques (image forensics). The system will allow for an improved LC/LU annotation and ensure the process is untampered. (iv) Implement a Green Compliance toolbox, integrated with the paying agencies’ aforementioned tools. This will benefit from (a) low-cost spectral sensors measuring soil quality and assessing the status of land-degradation in the land parcels and (b) an ML-based inferencing system deployed on a larger scale (regional, national) to quantify the levels of some of the monitored parameters and consequently extract tangible environmental performance metrics for an entire region
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The information about "DIONE" are provided by the European Opendata Portal: CORDIS opendata.
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