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National-Scale In-Season Field Boundaries of Ukraine Using Remote Sensing.

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Accurate agricultural field boundaries were mapped across Ukraine using satellite imagery. This dataset supports crucial analyses for food security and farm management, even amidst conflict.

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Area of Science:

  • Agricultural Science
  • Remote Sensing
  • Geospatial Analysis

Background:

  • Field boundaries are critical for agricultural spatial analysis, including crop mapping and yield prediction.
  • Timely and accurate field boundary data are essential, especially in dynamic geopolitical situations.
  • Existing methods may not meet the demand for in-season, high-resolution boundary information.

Purpose of the Study:

  • To generate a comprehensive dataset of delineated agricultural field boundaries across Ukraine.
  • To develop and validate a methodology for accurate, in-season field boundary delineation using satellite data.
  • To provide crucial data for agricultural monitoring, food security assessments, and humanitarian aid efforts.

Main Methods:

  • Utilized time-series of high-resolution PlanetScope satellite imagery (3-meter resolution).
  • Employed bi-weekly image composites processed via Google Earth Engine for delineation.
  • Validated delineations against a reference dataset of 12,331 Global Navigation Satellite System (GNSS) derived field boundaries.

Main Results:

  • Successfully delineated over 5 million agricultural fields in Ukraine for the 2021-2023 period.
  • Achieved high accuracy in field boundary delineation, validated against GNSS data.
  • The developed method demonstrates robustness and applicability for large-scale agricultural monitoring.

Conclusions:

  • The generated dataset provides invaluable, up-to-date information on agricultural land use in Ukraine.
  • The methodology offers a scalable and accurate solution for agricultural field boundary mapping.
  • This data supports informed decision-making in agriculture, food security, and policy development.