AI-Assisted Mapping Tool for Disaster Management

Challenge

Humanitarian organizations often face the challenge of mapping disaster-affected areas quickly and accurately. This is essential for planning and coordinating relief efforts. However, traditional mapping methods can be time-consuming and labor-intensive, especially in remote or inaccessible areas.

Solution

Omdena developed an AI-assisted mapping tool to help humanitarian organizations improve the accuracy and efficiency of their mapping efforts. The tool uses convolutional neural networks (CNNs) to automatically detect building footprints from aerial images. This allows humanitarian organizations to map large areas quickly and easily, even in remote or inaccessible areas.

Results

The AI-assisted mapping tool has been used by humanitarian organizations to map disaster-affected areas in a number of countries, including Haiti, Nepal, and the Philippines. The tool has been shown to be highly accurate in detecting building footprints from aerial images, with an average accuracy of around 94%.

Benefits

The AI-assisted mapping tool has a number of potential benefits for humanitarian organizations, including:

• Improved accuracy and efficiency of mapping efforts: The tool can help humanitarian organizations to map disaster-affected areas more quickly and accurately than traditional mapping methods. This can lead to better decision-making and more effective relief efforts.
• Increased availability of map data: The tool can help humanitarian organizations to collect map data in remote or inaccessible areas where traditional mapping methods are not feasible. This can lead to a better understanding of the needs of the affected population and more effective relief efforts.
• Reduced costs: The tool can help humanitarian organizations to reduce the costs of mapping efforts. This is because the tool can automatically detect building footprints from aerial images, which eliminates the need for manual digitization.

Conclusion

The AI-assisted mapping tool developed by Omdena is a promising new technology that has the potential to improve the efficiency and effectiveness of humanitarian organizations. The tool can be being used by humanitarian organizations around the world to map disaster-affected areas.

One example of how the AI-assisted mapping tool has been used to improve humanitarian response is in Haiti. In 2021, Haiti was hit by a powerful earthquake that caused widespread damage. The AI-assisted mapping tool was used to quickly map the affected areas, which helped humanitarian organizations to identify and prioritize areas that needed assistance. The tool also helped humanitarian organizations to coordinate their relief efforts and to track their progress.

The AI-assisted mapping tool is a valuable tool for humanitarian organizations. It can help them to improve the accuracy and efficiency of their mapping efforts, increase the availability of map data, and reduce costs.

Successful Project between Omdena and The Humanitarian OpenStreetMap Team (HOT)

In collaboration with HOT, Omdena developed an AI-assisted mapping tool to address the challenge of missing map data in disaster-prone areas. By leveraging deep neural networks and pre-trained models, the project achieved an average prediction accuracy of around 94% and an Intersection over Union score of around 84%. The project’s outcomes include the development of the HOTLib library, enabling HOT to provide their mappers with an AI-assisted collaborative mapping tool.

Find more information about page project here!

Read more about technical case study here!