Past Winners

The Team is composed of two PhD students and a post-doctoral research fellow at Teagasc Agriculture and Food Development Authority of Ireland, the national body providing integrated research, advisory and training services to the agriculture and food industry and rural communities.

Azucena Jiménez Castañeda: PhD student (2nd year) at Teagasc Food Research Centre, Ashtown in Dublin and Maynooth University, Ireland. Her research interests include meteorological radar, and statistics. Currently, she is working on chain radar signal processing to use meteorological nowcasting techniques to detect rainfall for real time agricultural advice.

Gabriela Mihaela Afrasinei: is a geographer from a picturesque city on the Danube in south-east Romania, with a PhD in Environmental Sciences awarded in Italy. Currently she is a post-doctoral research fellow at Teagasc Food Research Centre, Ashtown in Dublin. Her research focuses on the use of remote sensing and geospatial analysis for land cover, land use and soil mapping and classification, and land degradation assessment.

Richa Marwaha: is a PhD student (2nd year) at Teagasc Food Research Centre, Ashtown in Dublin and UCC, Cork. Her research interests include remote sensing and satellite image processing. Currently, she is working on grassland biomass estimation using machine learning algorithms.

In the meat and dairy sectors across Atlantic Europe sustainable livestock farming requires proper grassland management. We propose “Feed On DemanD - wEdge & gRazing App” - FODDERApp, a satellite-based mobile application to support efficient farm management. This webGIS platform automatically acquires and processes latest available Copernicus Sentinel-1, Sentinel-2 and meteorological data (near real-time) to estimate above-ground biomass on a per-field basis employing proven machine learning algorithms.

Jon Bruno is a PhD candidate in ionospheric tomography at the University of Bath and conducts research on ionospheric tomography and data assimilation.

Brian Weaver and Kai Guo are both PhDs in civil engineering at the University of Nottingham, Kai conducts research on ionospheric scintillation sensitive tracking models and mitigation tools, While Brian studies PPP and RTK algorithm development.

Paola Testa is a PhD student in strategy at the Toulouse Business School, where she conducts research on the diffusion of innovation and strategic marketing in the context of the space economy.

The authors are Early Stage Researchers (ESRs) of the TREASURE project, a prestigious Marie Sk?odowska-Curie Actions (MSCA) Innovative Training Network (ITN), funded through the European Union’s Horizon 2020 Research and Innovation Programme. TREASURE is a very international team composed of PhD students spread all around Europe.

The European Earth Observation satellites are powerful tools which can help to perform precision agriculture. Space and time variability of crops and soil features can be detected by several instruments mainly represented by proximal and remote sensing. Proximal sensors allow detection of crop or soil features with a sub-metre resolution, but they are often expensive. On the other hand, remote sensing allows detection of a large quantity of information quickly and relatively cheaply.

Several studies have shown the usefulness of Sentinel-1 or Sentinel-2 satellites, but a methodology that takes advantage of both sensors is not clear.  Electromagnetic sensor (EMI) data can be integrated with soil sampling and vegetation mapping by NDVI to draw a prescription map for nitrogen fertilisation. Data fusion from different satellites can take advantage of increased spectral and temporal resolutions. 

This work shows two innovative data management approaches: (1) The use of backscattering coefficient for soil properties in centre pivot system, and (2) the use of the correlation coefficient to evaluate the NDVI trend during the growing season.