In the wake of a disaster, Disaster Maps share real-time information with response teams, helping them determine things like whether communities have access to power and cellular networks, if they have evacuated, and what services and supplies they need most.
Disaster Maps use statistical techniques to maintain individuals' privacy. For example, we only share privacy-protected information and also add up data points in a given area (called a map 'cell' or a 'tile') to prevent re-identification. If there are only a few individuals in an area, we also smooth populations across tiles, meaning that we average the number of people in a given area with nearby areas, making it even harder to re-identify anyone.
Disaster Maps can be generated within 24 hours of a natural disaster — much faster than comparable tools— and update daily as the situation on the ground unfolds. This allows agencies to respond to changing circumstances in evacuations, connectivity, or supply needs.
Since the launch of Disaster Maps in June 2017, we have generated data for 100+ natural disasters, helping to guide response efforts around the world. During the 2018 hurricane season, our maps informed active disaster recovery in India, Guatemala, Indonesia, the Philippines, California, North Carolina, Florida, and other disaster-affected locations around the world.
Who Uses Disaster Maps
International agencies and UN organizations like UNICEF and the World Food Programme use Disaster Maps data to guide their local deployments to disaster-affected areas and support local governments in their response efforts.
Domestic organizations like the American Red Cross, SEEDS India, and Humanity Road use Disaster Maps to support their local communities, track evacuations, and route supplies to the areas that need them most.
Universities and researchers
Universities and researchers use Disaster Maps to analyze how disaster-affected populations are using social services, whether they evacuate based on official orders, and how social ties affect their resilience after a disaster.
Quantifying the dynamics of migration after Hurricane Maria in Puerto Rico
Understanding the population composition and distribution of a region affected by a major natural disaster is vital for the allocation of resources to communities in need and critical to inform mortality estimates. The utilization of social media traces, coupled with mobile phone data, could provide live estimates of post-disaster population changes in disaster-affected areas.
Many Displaced from Hurricane Laura Are Now in Path of Hurricane Delta
Hurricane Delta is set to make landfall as a Category 2 storm on the coast of Louisiana and western Mississippi on Friday, Oct. 9. This would be a serious situation under any circumstance, but for those still displaced from the last major storm in this area, Hurricane Laura, which made landfall on Aug. 26, the impact is likely to be doubly hard. According to the best available estimates roughly 8,000 homes were damaged during the impact of Hurricane Laura, and many people have yet to return.
The 2019-2020 Australian Bushfires: From Temporary Evacuation to Longer-term Displacement
Bushfires that raged across Australia triggered around 65,000 new displacements between July 2019 - February 2020. They also destroyed more than 3,100 homes, potentially leading to longer-term displacement for thousands of people. This report presents the first comprehensive figures and analysis of the patterns of displacement associated with the 2019 - 2020 bushfire season.
Displacement, Gender Disparities, and Shelter Utilization after Hurricane Laura
Data from Facebook and Camber Systems highlights patterns of movement as people moved to shelter from the hurricanes that landed on the Gulf Coast in the early part of September. First, we can see the estimated change in the population of devices from Facebook data. The difference in densities between counties can be seen by comparing the percentage change of the population with an estimated absolute change extrapolated using the American Community Survey (ACS) data from the US Census.
In the News
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