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Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
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Building a community-based open harmonised reference data repository for global crop mapping.

Hendrik Boogaard1, Arun Kumar Pratihast1, Juan Carlos Laso Bayas2

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Summary
This summary is machine-generated.

A new open-access repository of harmonized crop reference data (over 75 million observations) is now available globally. This initiative supports the development and validation of accurate crop type and cropland mapping products.

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Area of Science:

  • Earth Science
  • Agricultural Science
  • Data Science

Background:

  • Reliable crop type and cropland maps depend on high-quality reference data.
  • Collecting and harmonizing diverse crop reference data globally presents significant challenges, including data sharing restrictions.

Purpose of the Study:

  • To establish a community-based, open, and harmonized global reference data repository.
  • To facilitate model training and product validation for agricultural Earth Observation.

Main Methods:

  • Aggregated and harmonized data from various sources including GEOGLAM JECAM, Radiant MLHub, CGIAR, NASA Harvest, and citizen science platforms.
  • Collected and standardized data from 2016 onwards, assessing spatial, temporal, and thematic quality.
  • Developed a repository with standardized metadata, making a substantial portion publicly accessible.

Main Results:

  • Created a global repository containing approximately 75 million harmonized crop observations.
  • Ensured data quality through rigorous assessment rules.
  • A significant portion of the harmonized data is publicly available for use.

Conclusions:

  • The repository provides a valuable resource for calibrating deep learning algorithms and validating Earth Observation products for crop monitoring.
  • Continued support and institutionalization of this open data initiative are recommended to foster advancements in agricultural monitoring.