Participate now in the GEO-AI Challenge for Cropland Mapping
DESCRIPTION
Timely and accurate crop maps are essential for various applications in agriculture as well as other relevant research fields, such as natural resources, environment, health, and sustainability. Cropland extent maps are the basic products for the practical agricultural applications. Numerous algorithms have been proposed for cropland mapping using satellite observations, and several freely available land cover products provide global cropland extent maps at a 30m resolution, such as WorldCover, Globaland30 and GFSAD30. However, the data have several limitations: (1) the data are not updated annually, limiting their usefulness for monitoring changes over time; (2) each product have its own definition of “cropland”, which differs from FAOSATA’s definition of “6620 cropland” or “6621 arable land”; (3) the existing global cropland masks have significant disagreement.
With several new earth observation plans implemented and others to be implemented soon, more satellite imagery with increasing spatial and temporal resolution are available. Machine learning and artificial intelligence promise to improve the accuracy and robustness of land cover classification with satellite images.
To address these challenges and advance the mission of global high-resolution cropland extent mapping using remote sensing data, this challenge aims to develop accurate and cost-effective classification models for cropland extent mapping with machine learning techniques. By participating in this challenge, researchers and practitioners can contribute to the advancement of global cropland mapping, enabling more precise and comprehensive understanding of agricultural landscapes worldwide.
Objectives
1. Developing methods for annually cropland extent mapping at 10 m resolution.
2. Testing the temporal extendibility of the proposed method at local scale.
About AI for Good - International Telecommunication Union (ITU)
AI for Good is organized by ITU in partnership with 40 UN Sister Agencies. The goal of AI for Good is to identify practical applications of AI to advance the United Nations Sustainable Development Goals and scale those solutions for global impact. It’s the leading action-oriented, global & inclusive United Nations platform on AI.
Learn more about the AI for Good initiative here.
Read more about the evaluation process of the challenge, the prizes, the timeline and how to participate here.
Competition closes on 5 October 2023. Final submissions must be received by 11:59 PM GMT.
This challenge is a work of the UN Open GIS group, initiated by FAO, ITU and UNOCD.
Learn more about the work of the UN Open GIS Initiative here.