A Machine learning approach for rapid disaster response based on multi- modal data: The case of housing & shelter needs

Along with climate change, more frequent extreme events, such as flooding and tropical cyclones, threaten the livelihoods and wellbeing of poor and vulnerable populations. One of the most immediate needs of people affected by a disaster is finding shelter. While the proliferation of data on disasters is already helping to save lives, identifying...

Humanitarian access, interrupted: dynamic near real-time network analytics and mapping for reaching communities in disaster-affected countries

In the immediate aftermath of a disaster, local and international aid organisations deploy to deliver life-saving aid to the affected population. Yet pre-disaster road maps and road transportation models do not capture disruptions to the transportation network caused by the disaster or the dynamic changes of the situation, resulting in...

Towards coordinated self-organization: An actor-centered framework for the design of disaster management information systems

Traditionally, disaster management information systems have been designed to facilitate communication and coordination along stable hierarchical lines and roles. However, to support coordination in disaster response, disaster management information systems need to cater for the emerging roles, responsibilities and information needs of the...