Maybe. Maybe not. But in sustainability terms, there is no doubt that big data is currently making a very solid contribution. In this second article in our “AI for good” series, we’re looking at how the use of big data – combined with AI and ML – is helping to achieve and maintain momentum when it comes to sustainability.

Big data as a hero for the environment

As the world of big data evolves we are increasingly seeing it being rolled out for so much more than just commercial enterprise. In the context of the environment, big data – combined with AI and ML, the key enabler technologies of big data analysis – has the power to provide us with insights about the state of the natural world around us. Being able to capture, process, analyse and visualise large datasets in a short time frame has given scientists increasingly detailed understanding of what’s happening to the environment, from projects that are focused on a micro level to those that cover a vast, global area. And it’s not just about piling on the gloom and doom because big data is also being used to reveal where there is cause for hope among broad patterns of decline.

How has big data had an impact?

• Monitoring changes to environments, e.g. Arctic ice. A collaboration between NASA and the European Space Agency combined data on the changing volume, flow and gravitational attraction of ice sheets to model surface mass balance. It revealed that Greenland lost 3.8 trillion tonnes of ice between 1992 and 2018 – enough to push global sea level up by 10.6 millimetres.
• Identifying ecosystems that are the most under threat. Multiple lines of evidence have been integrated to assess the threat status of ecosystems and design various ‘red lists.’ This has been used to highlight problems, such as 85% of the forest area – and 80% of forest types – being threatened in the Caribbean and Americas.
• Generating green data that companies can use to minimise their impact on the environment. Big data is vital for sustainability reports and the strategies that organisations can adopt to optimise energy management and resources, minimise production-based emissions, anticipate repair needs and monitor machinery.
• Highlighting where human efforts have made a big difference. For example, efforts at land management in India and China have had a major impact greening large areas. This achievement was identified through analysis of recent satellite data. A similar process has also been used to establish the effectiveness of changes to legal frameworks to protect forests in areas such as Brazil.

Examples of big data projects that are making a difference

Aqueduct

This water resources mapping tool was developed by the World Resources Institute. Its purpose is to monitor water and calculate risks and it can do this in any location anywhere in the world. Key to the way Aqueduct functions is the big data it is fed about water, from the way that regulatory changes are making an impact to information on water quality and quantity.

REMAP

This application uses Google Earth data to map land cover change. Being able to monitor land use and change supports conservation and sustainability in a number of key ways, including, creating biodiversity inventories, highlighting ecosystem diversity hotspots, mapping ecosystem loss at local scales and supporting environmental education initiatives.

Copernicus

This is a satellite based observation programme for the EU that analyses data to inform key decisions around optimising water resource management, biodiversity, air quality, fishing and agriculture.

Trash track

This is designed to use data from sensors to get a clearer picture of recycling pathways. We know so much about supply chains but so little about the ‘removal’ chain – this is the problem Trash Track is designed to solve. It focuses on how pervasive technologies can expose the challenges of waste management and sustainability – and using these technologies to make 100% recycling a reality.

Breathe London

This UK project measures and maps Londoners’ daily exposure to air pollution using data drawn from a network of advanced air pollution sensors deployed across the city.

We need more data

It seems incredible to say, given the vast increase in the volume of data in the past five years. However, when it comes to sustainability, we need more of it. The UN’s Environment Programme (UNEP) identified that for 68% of environment-related Sustainable Development Goal indicators, there is not enough data to assess progress. At a recent UNEP event, participants couldn’t stress highly enough how much big data, AI, ML and IoT could speed up progress on environmental goals – as long as input continues.

As always with big data it’s what you do with it that counts. Every one of these projects provides the kind of insight that could be used to change the path that we’re all currently on when it comes to climate change. The key will be sustaining the momentum around taking action to achieve sustainability goals, something that big data has a great deal of power to influence.