Analysing data to gain geographical or spatial insights has untapped potential which can boost business, change lives and protect the environment
01 Predicting flu outbreaks
GlaxoSmithKline (GSK) wanted to anticipate flu outbreaks in Indonesia to create targeted advertising campaigns for relevant vitamin supplements. To do this, consumer behaviour predictions agency Black Swan used geospatial data derived from social media, such as people complaining of cold and flu online. The agency used this with local weather data, and GSK and government historic prescription information to build a geospatial data model, supported by artificial intelligence, that could accurately predict cold and flu outbreaks across the country four to five days before they became known to local authorities.
According to Steve King, chief executive at Black Swan, deciphering location data from social media was important, but challenging, as it often had to be “enriched with locational clues and mined harder to understand the geographic elements that were not baked in”.
When fully functional, the algorithm was linked to marketing servers, so that when an outbreak was anticipated in a particular town, localised adverts promoting relevant vitamin supplements were purchased on mass to encourage people to stock up.
The model, which cost around £80,000 to build, was later provided free to the NHS to predict cold and flu outbreaks to improve management of A&E waiting times.
02 Preserving forests
Global deforestation reached a record 29.7 million hectares in 2016, according to data from the University of Maryland. The UK Space Agency-funded, £14-million Forest 2020 initiative, being developed by Ecometrica, aims to tackle this problem by using geospatial data to monitor 300 million hectares of tropical forests in Indonesia, Brazil, Colombia, Mexico, Ghana and Kenya for illegal mining, logging and fires.
The company harnesses remote georeferenced data from satellites, including the European Space Agency’s Sentinel satellites, drones, corporate area networks and social media, which is then analysed in real time using machine-learning and artificial intelligence, and sent to the web browsers of relevant agencies in the partner countries.
The bi-weekly refreshed data creates an up-to-date picture of what is happening on the ground to reduce response times from weeks to days, compared with traditional methods of surveying land with helicopters.
The model could soon be used to monitor natural disaster risk and response, says Gary Davis, chief executive of Ecometrica. “This creates opportunities for everyone to use geospatial data, regardless of their expertise,” he says.