On the heels of the data revolution, Earth and environmental science is undergoing a model revolution. This revolution brings together disparate researchers to harvest scientific understanding from the data deluge. This is certainly true at the intersection of geospatial data science, environmental science, and statistics/machine learning. The next generation of models will be developed collaboratively by domain-experts and data scientists/statisticians, and must scale to massive data, leverage spatiotemporal coherence in heterogeneous data, embed scientific knowledge, and answer science questions.
Long-term monitoring data indicate that the largest wildfires are getting larger on average each year in the United States.
To understand why, an interdisciplinary team of fire ecologists, climate scientists, geomorphologists, and data scientists at Earth Lab and other institutions collaborated to build a predictive model of extreme wildfire events. We built the model with one simple idea: the size of the largest fire in a region is affected by two things: 1) the total number of wildfires ignited, and 2) the distribution of fire sizes within the region. We found that temperature and dryness nonlinearly relates to the likelihood of an extreme fire via these ignition and size pathways. Further, we found that because these effects are nonlinear, even a small amount of drying in an already dry region can lead to a substantial increase in the chance of an extreme wildfire event. For more, see Joseph et al. (2019).
Models allow us to link observed data back to the hidden rules of nature, and predict what might happen in the future. In the age of big data, we are now ushering in the next phase of scientific research that leverages big models to extract insight from the raw material provided by Earth observation data.
Dr. E. Natasha Stavros is the Director of Earth Lab Analytics Hub. She specializes in complex systems science, data science, image processing, and information technologies. She developed these skills as a fire ecologist, but has applied them in other complex systems including NASA Flight Projects, biodiversity science, and urban ecology.