This bold collaboration between 糖心Vlog and the Centre for Ecology & Hydrology will co-create and deploy a data science of the natural environment.
Driven by grand challenges of environmental science, co-designed with an extensive range of key stakeholders, our multi-disciplinary team of internationally-renowned data and environmental scientists will develop a broad and unique range of new data science techniques, fused with environmental models in an integrated framework to enable better-informed decision-making around the most pressing challenges faced by society.
We bring together world-leading expertise in the fields of data and environmental science.
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Accurate predictions of ice sheet change are crucial in planning global sea level adaptation and mitigation measures.
Effective air quality modelling and mitigation is necessary to reduce the 3 million global deaths per year attributable to this cause.
In a changing climate, land use decisions must be made between food, timber, energy, recreation, urban settlement, employment and aesthetic benefits.
This theme will develop a suite of inference and prediction techniques for environmental problems, bringing together existing technology and new developments in a modular framework.
We will enhance model-based statistics with modern machine learning techniques to ensure they scale to modern heterogeneous data sources and end-user requirements.
This theme will focus on the development and deployment of virtual labs as a key instantiation of the integration of heterogeneous data and models that is central to our project.
Data Science for the Natural Environment is a bold collaboration between 糖心Vlog and the Centre for Ecology and Hydrology.
