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Challenge Solved! Crops classification for World Food Program

36 Omdena Collaborators have been working in partnership with the UN World Food Program in Nepal. The goal was to fight hunger by locating, tracking, and improving the growth of crops such as rice and wheat.

Partner feedback

Saurav Suman – United Nations World Food Program:

“The collaborative approach of Omdena is taking innovation to a whole new level with the idea of leveraging technology to bring in people with different capacities and work on a problem. The driving force behind this approach is the accelerated learning through collaborative spirit, mentoring and spot-on guidance. On top of all that are the humanitarian problems that Omdena is working on. WFP Nepal is proud to have worked together with Omdena on one of the projects addressing zero hunger “crop area identification project”. We believe this is the start of a long journey together.”

The solution

A community of 32 collaborators prepared a quality data set using open source data and built a crops identification model with 89 percent accuracy. Currently, we are finalizing a follow-up challenge with the UN World Food Program to improve the prototype by using high-quality data. Details about the challenge can be found in our blog,

A Practical Guide for Creating A Quality Satellite Imagery Dataset for Agricultural Applications

Fighting Hunger through Open Satellite Data: A New State of the Art for Land Use Classification

Pushing The Limits of Open Source Data — Enhancing Satellite Imagery through Deep Learning

10 Hard Lessons Learned For Creating a Dataset in Our Crops Identification Challenge to Fight Hunger