Crowdsourcing, coupled with the proliferation of mobile technology and social media, is rapidly changing the face of disaster response. Crowdsourcing combines the two words “crowd” and “outsourcing” and refers to the idea of tapping into the unlimited resource pool of public intelligence to gather information and perform tasks that would otherwise be limited or outsourced to a few actors. This technological clout is being increasingly felt in the world of disaster response. By pooling the contributions of the many to pinpoint trouble areas, gather critical information, and perform time-sensitive tasks, crowdsourcing can serve as a dynamic tool and nexus for collaboration for on-the-ground responders, policy decision makers, and researchers during humanitarian emergencies.

Access to, and management of, data is a critical element in disaster planning and response. For response agencies and governments, some of the greatest hurdles in disaster response include the lack of organization, coordination, and information management. During a natural disaster, emergency responders must understand, but often lack, information reflecting real-time movements on the ground in order to identify and prioritize needs and coordinate service delivery. Crowdsourcing taps into the collective intelligence and capabilities of the public, including victims on the ground and volunteers from all over the world. Crowdsourced data helps fill the information gap and provides responders with contextualized, real-time information in disaster areas where conditions and needs on the ground are constantly shifting. Crowdsourcing also carries the unique advantage of capturing direct feedback from beneficiaries and leveraging local intelligence that often gets overshadowed by other information sources.

After the Haiti earthquake in 2010, thousands of affected Haitians and volunteers with access to a cell phones or laptop mobilized to create comprehensive, real-time maps, translate SMS messages from Haitian Creole to English, and identify specific emergencies, all for little to no cost. The collaborative efforts of the public at large contributed to the work of humanitarian workers by allowing them to target, accelerate, and coordinate response efforts. The remarkable display of crowdsourced work reflects a shift away from exclusively traditional information-gathering approaches and acknowledges the power in number through mass collaboration.

Since Haiti, crowdsourcing disaster response has grown in sophistication and organization, and mainstream humanitarian organizations like Médecins Sans Frontières (Doctors Without Borders) and Office for the Coordination of Humanitarian Affairs (OCHA) are integrating crowdsourced data with traditional sources in their response efforts, like after Typhoon Haiyan in the Philippines. Crowdsourcing has paved the way for non-experts and volunteers to act as “digital humanitarians,” “crisis mappers,” and key contributors to disaster response and knowledge management, alongside more established players such as national space agencies and commercial satellite-image providers.

As crowdsourcing technology advances, software companies are partnering with other stakeholders to find new and creative ways to gather user-generated data in order to track and provide real-time alerts on weather patterns and damages caused by natural hazards such as floods, earthquakes, and tornadoes. Moving forward, crowdsourcing will continue to play an important and dynamic role in strengthening disaster risk management and achieving greater levels of community preparedness.

Crowdsourcing, according to, has been a popular crisis mapping tool. “Used to map a wide range of issues, crowdsourcing makes it easier for a large group of people from all over a region, city, country, etc., to document where problems are occurring and when. This information is used to help respond to problems, provide aid to regions that need it and keep the public up-to-date on issues as they progress.”

Crisis mapping, according to, is “the real-time gathering, display and analysis of data during a crisis, usually a natural disaster or social/political conflict (violence, elections, etc.).”