Project Title: Agri-Environmental Big Data analytics via WebGIS: Geospatial data obfuscation and modelling of crop growth and productivity
Overview: The key objectives of this project :
1. Perform an extensive comparison of spatial data obfuscation methods on Irish agricultural data that is subject to data protection regulations.
2. Test Teagasc developed crop growth/ yield models for winter wheat and spring barley in a geospatial environment.
3. Develop a machine learning methodology that incorporates spatial data obfuscation methods to predict crop suitability and yield at both a farm- and national-level.
4. Demonstrate the utility of obfuscation and machine learning through webGIS big data analytics to predict yields for several commercially important crops.
2018 Research MEngSc in Civil & Environment Engineering (Hydrological Modelling), University College Cork (UCC), Ireland
2015 Higher Diploma in Sciences in Data Sciences & Analytics, Cork Institute of Technology (CIT)
2013 MSc in Mathematical Modelling and Scientific Computing), University College Cork (UCC)
Programme Area: Crops, Environment and Land Use
Supervisors: Dr.David Wall and Dr. Paul Holloway
Location: University College Cork (UCC) and Johnstown Castle, Wexford
Funding Source: Teagasc