Joint activities, such as capacity-building and the demonstration project between the members of the Agriculture sector and the advanced partner (NOA), targeting the enhancement of the research skills and knowledge have been carried out. Furthermore, a summary of other activities related to the sector is given describing the stakeholders’ engagement – living labs; the development of the beta-version of the ERATOSTHENES CoE Agri Nexus Hub is also provided.

Following the above-mentioned Agriculture capacity-building activities, a demonstration project followed on “Agriculture Monitoring” with the support of NOA. Various technologies were transferred to ERATOSTHENES CoE’s personnel such as databases and data querying, Causal ML, Data Cube implementation and experience related to agricultural practices, yield prediction, soil degradation and ecosystem services indicators. The transfer of knowledge aims to support ERATOSTHENES CoE personnel to demonstrate its capacity for agricultural monitoring and machine learning techniques to assist in agricultural decision-making. 

In brief, the activities and research topics of the Agriculture sector are the following:

The “Agriculture Monitoring” demonstration project acts as a knowledge-transfer tool dedicated to highlight and advance the research capabilities of the ERATOSTHENES CoE. NOA and ERATOSTHENES CoE staff worked together closely, developing capacity, critical workflows from data to core outputs to produce new scientific knowledge and practical advice on crop and agricultural practice (irrigation, ploughing etc.) suitability. 

Through the demonstration project, the agriculture data cube of the ERATOSTHENES CoE was initiated where different Analysis Ready Data (ARD) satellite products were ingested such as Sentinel 1 & 2 satellite imagery data (pre-processed) as well as five different MODIS products (1. Vegetation Indices 16-Day L3 Global 250 m; 2. Vegetation Continuous Fields Yearly L3 Global 250 m, 3. Leaf Area Index/FPAR 8-Day L4 Global 500 m; 4. Burned Area Monthly L3 Global 500 m; and 5. Land Surface Phenology (Land Cover Dynamics) Yearly L3 Global 500 m). Additionally, during the Agriculture demonstration project, crop suitability maps were developed, incorporating information on barley, wheat, crop diversification, and fallow suitability. To assess the accuracy and reliability of these derived crop suitability maps, field-scale hydrogeological models were developed. These models were utilised to estimate irrigation demand, allowing for an evaluation of the associated uncertainty of the derived suitability indices. This approach enabled a thorough assessment of the suitability maps and their applicability in agricultural decision-making processes. The capacity-building activities, the demonstration project and input by the continuously increasing Agriculture team led to the development of the Agri Nexus Hub, presented below.

The ERATOSTHENES CoE Agri Nexus Hub: The Agroclimatic Observations Tool utilises data acquired from meteorological stations of the Department of Meteorology of Cyprus, the Copernicus Atmosphere Monitoring Service, Satellite Imagery from Sentinel-2, LPIS from the Cyprus Agriculture Payment Organization and in-situ observations such as spectroradiometric data, Leaf Area Index, Meteorological data from local weather stations, etc. The objective of this tool is to inform farmers daily about the water losses of their fields due to climatic conditions. Agroclimatic Observations provides also daily calculations of Crop Evapotranspiration (ETc) for citrus orchards, olive groves and potatoes cultivations around Cyprus. Sentinel-2 Normalized Difference Vegetation Index (NDVI) is beneficial to understanding the vegetation’s health in the island’s territory. This is the first phase of the development of the ERATOSTHENES CoE Agri Nexus Hub, which will be open access for stakeholders and end users; in contrast, a second phase (validation phase) of collecting in-situ data will follow, aiming to validate the estimated irrigation demand.

agriculture sector activities
This project has received funding from the Government of the Republic of Cyprus through the “Directorate General for European Programmes, Coordination and and Development”.
This project has received funding from the European Union’s “Horizon 2020 Research and Innovation Programme” under Grant Agreement No 857510”.
This project is co-funded by the Cyprus University of Technology.