The project will explore how state-of-the-art Earth Observation (EO) based monitoring tools and decision support systems, may enable growth of the livestock sector while also addressing important sustainability issues. Through a literature review, it will compile a comprehensive dataset for spatiotemporal scenarios of their implementation in livestock production.
Department: Sustainable Land Management
Supervised by: Dr. Georgios Pexas
Conventional, large-scale, livestock production systems are complex systems embedding activities such as animal feed production, animal health & growth management, manure management and waste disposal. Many of these system components are associated with significant negative impacts on sustainability of the agri-food sector, including environmental, economic, social, and food safety implications. While Earth Observation (EO) based technological solutions have been developed to enable sustainable intensification of crop production, little has been researched in relation to the effectiveness of such tools to support sustainable development of livestock production. This project aims to extend existing knowledge on the potential for EO technologies to facilitate monitoring of impacts to sustainability by livestock systems, and support decision making at regional scales and on a farm level. This overarching aim will be achieved through the following specific objectives: i) Identify key sustainability challenges associated with conventional livestock production, ii) Identify state-of-the-art EO-based monitoring and decision support systems adopted in livestock production, iii) Identify gaps in current service provision for remote and accurate monitoring of livestock production iv) Compile secondary data from literature to support the modelling of scenarios to assess improvements on sustainability of livestock production systems by implemented EO-based technologies at different spatiotemporal scales To realise the aim and objectives of the project, the student will research extensive relevant scientific and grey literature. They will further develop a questionnaire-based survey regarding user-requirements of livestock producers, regulatory authorities and research institutes that could potentially use relevant EO-based technologies.
Collect scientific and grey literature on key sustainability issues of conventional large-scale livestock production. Collect scientific and grey literature on the role of state-of-the-art Earth Observation based monitoring tools and decision support systems for livestock production. Source from literature secondary data to support spatiotemporal-scenario modelling for the implementation of such tools in livestock production. Support the development of a questionnaire-based survey regarding user-requirements for EO-based monitoring and decision support tools. Support the synthesis of the information sourced from literature in a comprehensive report and data repository (e.g., list of data, details and sources – metadata in Excel).
Critical thinking. Ability to work independently. Interest in sustainability, specifically in environmental, economic and social issues associated with livestock production. Interest in Earth Observation and Life Cycle Sustainability Assessments. Ability to review and synthesise evidence. Good communication skills
The student will be able to develop their research and analytical skills, and scientific writing. They will have the opportunity to broaden their network and discuss with expert Earth Observation technology developers from Europe, through the on-going ENVISION H2020 project. Through this research and the specific outputs, the student will get an insight into state-of-the-art and scan towards the future directions of digital innovation for sustainable development of livestock production.
SAPD
Flexible (between 9-5 Monday-Friday)
Monday 12 June 2023 - Friday 21 July 2023
The deadline to apply for this opportunity is Monday 3rd April 2023. Students should submit their CV and Cover Letter directly to the Project Supervisor (click on supervisor name at the top of the page for email). Successful candidates will be invited for an interview.