With atmospheric carbon dioxide levels continuing to rise, Professor John Kimball talks about how Big Data can be used to answer the world’s most pressing environmental problems.
— by Louisa Wood
Climate change, deforestation, ocean acidification, pollution — the scale of human-induced environmental impacts on the Earth is now so profound that scientists have declared a new geological epoch, the Anthropocene.
Big Data has emerged as a game-changer for addressing and mitigating these impacts, thanks to the vast amounts of environmental data being collected and processed every day from a multitude of sources — from satellites and sensors to aircraft and weather station networks. Climate sciences are particularly leading this Big Data revolution, as recognized by the Data-Driven Climate Sciences section of Frontiers in Big Data.
We asked Professor John Kimball — the section’s Chief Editor and Professor in the Department of Ecosystem and Conservation Sciences at the University of Montana, USA — for his insights on what Big Data means for the environment and sustainability.
Is Big Data a key solution to the problems of the Anthropocene?
I think so. The ability to rapidly process and extract information from massive and diverse environmental data records provides a highly effective global monitoring system, which can aid in mitigating impacts from natural disasters to managing limited resources. Enhanced global monitoring and information can also provide early warning of potential ecosystem degradation, including changes in biodiversity, water quality, disease risk, vegetation stress and food security. This information can be used to allocate resources and planning efforts to reduce potential environmental damage before it’s too late.
Big Data is being increasingly used to address issues relating to the climate sciences. What examples strike you the most?
The climate sciences are experiencing exponential growth in the size and diversity of global environmental data acquired from diverse sources, including complex earth system models, remote weather stations, airborne and remote satellite sensing. Before the Big Data revolution, the collection, storage and processing of global environmental data required complex and centralized data storage and computing facilities that limited access for many potential users. For me, the real eye-opener on the value of Big Data has been the rapid growth in cloud-based public platforms and software that now give nearly any interested user the ability to access, process and analyze this data.
Big Data thus transcends political and social boundaries — delivering the power of information to the global community. This community includes less wealthy countries and populations in developing regions at greater risk from environmental degradation. These advances are therefore empowering people and organizations that have the greatest need for the information. By lowering cost and technical barriers to access and use of data and information, the Big Data revolution is driving rapid advances in the climate sciences and their societal benefits to a broad global community.
How are you using Big Data in your research?
As Director of the Numerical Terradynamic Simulation Group (NTSG), I use satellite remote sensing and ecological modelling to understand climatic impacts upon vegetation growth and water, carbon and energy cycles.
NTSG conducts research at a range of spatial scales, from landscape to global extents. Some recent projects include systematically mapping freshwater habitats for salmon across all major North Pacific rivers, developing new satellite capabilities for estimating cropland water use and productivity, and developing global satellite environmental data records that document recent changes in vegetation productivity and underlying environmental controls.
What is your vision for the Data-Driven Climate Sciences section of Frontiers in Big Data?
The climate sciences are really leading the Big Data revolution, driven by the need to effectively distill and utilize information from increasingly greater volumes of global data. New approaches that enhance data reduction and distillation processes are continuously developed, and environmental predictions and understanding are being improved by the information gained from large, diverse datasets. My aim for the section is really to provide a platform to showcase this ground-breaking interdisciplinary research — capitalizing on the Open Science framework to enhance the exchange of new ideas and information.
- Climate feedbacks
- Water and carbon cycle interactions
- Land-ocean-atmosphere connections
- Surface energy budget and climate change
- Earth observation and data processing technologies