Client Brief
- Because of the war, thousands of Syrians have fled their homeland to seek refuge in Lebanon
- Many of them live in informal rural settlements. Locating them and estimating their number is critical to the international community and actors wishing to support them
Solution
- Use advanced deep learning methods to identify the tents scattered across Lebanon on high-resolution satellite imagery
- Check the findings in the field with local consultants
- Based on this identification, follow the evolution (where ? how many ?) of the informal refugee settlements and assess their access to infrastructure (roads, markets)
Results
- Training of a Convolutional Neural Network with roughly 3,000 images distributed between tents/not tents areas
- Testing the algorithm on a batch of 1,000 other labeled images
- Accuracy: 90% of the tents are correctly identified