The SKAI isn’t the limit: How WFP uses satellite imagery and machine learning in emergencies

Overview of SKAI
SKAI is unique in having been trained with past-onset disasters that were previously tagged by manual analysts.
In the aftermath of a disaster, access to information is critical to allocate resources and reach people in need of assistance. In the photo: aerial image of Beira, Mozambique, after Cyclone Idai in 2019. Photo: WFP/INGC/Antonio Jose Beleza

Introducing SKAI

Approach: machine learning on satellite imagery

SKAI uses artificial intelligence to analyze satellite images to automatically assess damage post disasters.

Lessons learned from SKAI deployment in humanitarian operations

The destruction at Beirut’s port following a huge chemical explosion that devastated large parts of the Lebanese capital in 2020. Photo: WFP/Malak Jaafar

The way forward

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Sourcing, supporting and scaling high-impact innovations to disrupt hunger.

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