Spatial Data Science and Agriculture

Application Period: April 30, 2025 - May 3, 2025

Contact: internshipofficer.cs@mcgill.ca

Must be a current McGill student to apply.

Details of the research project:

  • Faculty, School, Department, and/or Unit: Department of Geography
  • Scope of the research project and your research needs: Our lab is working with various national and global scale agricultural datasets, including satellite remote sensing products that show the spatial distribution of different crop types. These crop classifications serve as the ‘backbone’ for various research applications such as describing cropping system diversity and diversification potential, examining the influence of urbanization on peri-urban agricultural lands, as well as for mapping fertilizer nutrient use and associated nutrient loading to the environment. To help facilitate these applications, we have a range of tasks around spatial data science, machine learning, and possibly even image processing. Some examples include but are not limited to:
    • testing different cropland typologies for Canada using multivariate clustering techniques with various agri-environmental data inputs at different spatial resolutions;
    • comparing different approaches to downscaling crop yield datasets;
    • testing different segmentation techniques (or existing outputs) to delineate crop field boundaries in Canada and how to allocate specific crop types to them based on existing crop classifications.
  • Objectives this research project accomplishes and/or helps contribute to: One or two specific spatial data science tasks will be chosen for the research project from on a range of options (based on interests, existing skills, etc.). During the summer, various methods/approaches/techniques will be compared using subsets of the data. Once the most promising approaches are identified, these will be applied to a larger dataset (e.g., an entire province of Canada, all of Canada, all croplands globally) for comparison. The reproducible workflow, including code (e.g., Python or R), will be archived. These outcomes from the summer research will directly contribute to ongoing research on agricultural sustainability and resilience in our lab and could lead to the possibility to collaborate on scientific publications down the road.
  • Required knowledge and skills:
    • Knowledge of Python or R, particularly for working with large spatial datasets.
    • Interest in applications of Computer Science to agriculture and environment.
  • Start and end date of research project: May 3, 2025 – August 18, 2025 (flexible)

Please submit a cover letter, cv, and your unofficial transcripts to internshipofficer.cs@mcgill.ca.