During disasters, there is a need for accurate, rapid, and reliable mapping, validation, and damage assessment to inform humanitarian response and recovery efforts. However, as disasters are often extensive in scale, it is important that these methodologies are scalable and can be employed for multiple affected areas at any point in time.

Crowdsourced mapping, validation, and damage assessment, when combined with multiple layers of validation with local knowledge, enables humanitarian actors to quickly reach multiple affected areas at once - ensuring that no one is left behind. Humanitarian OpenStreetMap Team (HOT) will cover the crowdsourced methodology piloted for the 2025 Myanmar Earthquake response, the outcomes, and the lessons learned.

There are pros and cons in applying different methodologies - AI-generated, expert-led, or crowdsourced - during a disaster. HOT sees value in employing a mixed-methods approach. This session will also explore the methodologies' benefits and limitations, and HOT's preliminary assessment of a mixed-methods model for future disaster response.