AI and Sentinel-2 Satellite Data for Crop Yield Estimation

SDG(s)

Sustainable Development Goal(s)

9Industry, innovation and infrastructure

12Responsible consumption and production

15Life on land

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Description of the solution

This solution is based on the use of Artificial Intelligence (AI) with Sentinel-2 satellite data to improve crop yield estimation. AI techniques like Machine Learning (ML) and Deep Learning (DL) are used to analyze high-resolution images from Sentinel-2, which capture information about crop health and growth. This data is then used to predict crop yields with greater accuracy. This approach can help farmers optimize resource use, reduce waste, and increase agricultural productivity.

Type of the Solution

Data_collection

Subcategory

Yield monitoring

Who led the solution

Other public institutions

Timeline for implementation

Short term (up to 1 year)

Lifespan of the solution

Long term (5 and above)

Additional notes

This is a study of different cases, led by the Karamanoglu Mehmetbey University, T√ºrkiye.

Link to the solution

Consent to share form or official link.

SDG(s)

Sustainable Development Goal(s)

9Industry, innovation and infrastructure

12Responsible consumption and production

15Life on land

Comments

Solution note