Multimodal Vision Research Laboratory

MVRL

Research Area: Agriculture

Agricultural applications within MVRL focus on global field boundary mapping and crop monitoring from satellite imagery. Highlights include the Fields of the World (FTW) benchmark and tooling for worldwide agricultural field boundary segmentation, plus methods for combining open labeled datasets across varying domains. See also our remote sensing and geospatial AI areas for related work.

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All Publications

  1. Muhawenayo G, Robinson C, Khanal S, Fang Z, Corley I, Wollam A, Gao T, Strnad L, Avery R, Estes L, Tárano AM, Jacobs N, Kerner H. 2026. PRUE: A Practical Recipe for Field Boundary Segmentation at Scale. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
    paper bibtex GeoAI Agriculture
  2. Thumbnail for The first global agricultural field boundary map at 10m resolution
    Robinson C, Muhawenayo G, Khanal S, Fang Z, Corley I, Tárano AM, Estes L, Marcus J, Jacobs N, Kerner H, Becker-Reshef I, Ferres JML. 2026. The first global agricultural field boundary map at 10m resolution.
    paper bibtex GeoAI Agriculture
  3. Thumbnail for Combining open labeled datasets with varying domains to improve large-scale agricultural field boundary delineation
    Balogun RO, Chakraborty T, Muhawenayo G, Kerner HR, Tárano AM, Fang Z, Jacobs N, Khanal S, Abedi R, Estes LD. 2025. Combining open labeled datasets with varying domains to improve large-scale agricultural field boundary delineation. In: American Geophysical Union (AGU) Fall Meeting Abstracts.
    paper bibtex Agriculture GeoAI
  4. Muhawenayo G, Fang Z, Khanal S, Wollam A, Corley I, Robinson C, Mohr M, Holmes C, Marcus J, Estes LD, Jacobs N, Tárano AM, Kerner HR. 2025. Global Field Boundary Delineation Model Zoo and Tooling. In: American Geophysical Union (AGU) Fall Meeting Abstracts.
    bibtex Agriculture GeoAI
  5. Mohr M, Roby M, Bosloper I, Kerner HR, Jacobs N, Robinson C. 2025. Fields of The World and fiboa: Towards interoperable worldwide agricultural field boundaries through standardization and machine-learning . In: Living Planet Symposium (LPS).
    bibtex Agriculture GeoAI
  6. Thumbnail for Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary Segmentation
    Kerner HR, Chaudhari S, Ghosh A, Robinson C, Ahmad A, Choi E, Jacobs N, Holmes C, Mohr M, Dodhia R, Ferres JML, Marcus J. 2025. Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary Segmentation. In: Association for the Advancement of Artificial Intelligence (AAAI).
    code website paper bibtex Agriculture GeoAI
  7. Kerner HR, Chaudhari S, Robinson C, Ghosh A, Ahmad A, Choi E, Jacobs N, Holmes C, Mohr M, Marcus J. 2024. Fields of The World (FTW!): A New Machine Learning Dataset for Agricultural Field Boundary Segmentation on Four Continents. In: American Geophysical Union (AGU) Fall Meeting Abstracts.
    bibtex Agriculture GeoAI