Great apes have disappeared from Gambia, Burkina Faso, Benin and Togo; a subspecies of Javan rhino went extinct in Vietnam in 2011 and the last western black rhinos have vanished from Cameroon; and up to 73 million sharks are killed a year for their fins. ITU explores the role of Big Data in preventing the illegal wildlife trade, to mark World Environment Day 2016 on 5 June.
The illegal wildlife trade has driven species to the brink of extinction and continues to endanger our global biodiversity. Though efforts to curb this activity have achieved some success, many animals are still at risk. This illegal activity has a wider socio-economic impact too, undermining economies, fueling organized crime, and feeding insecurity across the globe.
The need for innovative solutions and improved data to facilitate interventions to stop illegal wildlife trade has been noted by the United Nations and USAID-supported Wildlife Crime Tech Challenge.
Big data has the potential to fill this need. As noted by ITU News, “analysing more data in shorter spaces of time can lead to better, faster decisions in areas spanning finance, health and research.”
Big data is already being used to help stop wildlife crime around the world.
In 2011, 29% of fishing stocks were overfished and 61% were on the brink of being unsustainable. But due to the ocean’s vast expanse, it is difficult to police illegal activity. The Global Fishing Watch, a Google project in partnership with Oceana and SkyTruth, plots the position of thousands of fishing vessels worldwide in real-time, analyzing the GPS broadcasts of a ship’s location to determine its identity, speed and direction. This gives coastguards and regulators a wider scope of vision, helping them to track and monitor illegal activities, such as fishing in protected areas, more effectively.
Similarly, the Global Database of Events, Language and Tone (GDELT) Project monitors international news about wildlife and environmental crime to create a map tracking its global scale and impact. From 19 February to 2 June 2015 alone, nearly 30,000 articles were monitored and mapped. This comprehensive visualization gathers dispersed information to help understand global trends in wildlife crime and explain how local activities have a global impact.
In December 2014, ITU launched an Ebola-Info-Sharing app to help map and prevent the spread of Ebola. “On 28 August 2015, ITU launched in Freetown, Sierra-Leone a big data project to mitigate the Ebola disease in West Africa and across the world”, said Cosmas Zavazava, Chief of Department, Projects and Knowledge Management. It uses real-time location data which is anonymized to project individual privacy, analyzed, and visualized. “By monitoring travel in and out of affected areas, aid agencies can see what is happening on the ground and easily understand how a disease is spreading and quarantine exposed individuals and communities. This will not only save critical time when responding to a disease outbreak, but will potentially help to save millions of lives. ITU is rolling out a big data project for official statistics.”
Cosmas Zavazava said, “Our approach is to use big data, Internet of Things, and eventually artificial intelligence for environmental protection, climate change adaptation and mitigation, and for disaster management. In so doing, through these technologies we will be helping countries attain the global Sustainable Development Goals under the 2030 Development Agenda.”
The NASA Centre for Climate Simulation (NCCS) uses big data to study climate change. The data generated by the NCCS contributes to a variety of key research and policy papers such as IPCC’s Fifth Assessment Report, which can help policymakers develop appropriate strategies to respond to climate projections. Similar data mapping helped to forecast Hurricane Katrina, which helped to provide advanced warning and allow time for adequate preparations. [Learn more about NASA and big data here]
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