Deep data helps cities prepare for disaster

By Adam Green

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Reducing urban risk requires disaster-informed spatial planning, building codes and infrastructure, as well as clear plans for post-disaster response. This relies heavily on data that is often patchy or non-existent, especially in less-developed nations.

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However, disaster response experts have begun utilising non-traditional data sources to assist with planning. These include high-resolution images from satellites and drones, localised temperature and seismic intelligence from microsensors, and open data repositories such as social media activity to street maps from thousands of volunteer digital cartographers.

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Microsensors are also allowing scientists to build better forecasting models to predict how disasters might play out by giving them access to alternative data sets. One initiative called Tomorrow’s Cities is distributing hundreds of sensors in Istanbul, Kathmandu and Quito to gather data on ambient vibrations, such as rumbling trains or waves hitting a coastline.

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Tomorrow’s Cities also analyses earth observation data to run disaster scenarios. Using high-resolution satellite images, researchers create digital topography maps that show how artificial and natural structures might behave in a multi-hazard situation, such as landslides caused by an earthquake, which dump sediment into a river to cause flooding.

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