Data Science for Environmental Sustainability
Data analysis techniques are used to understand the current state of the environment by examining trends and looking for correlations between datasets. AI & ML can then be applied to automate tasks in analyzing large sets of data associated with various environmental concerns. Predictive analytics are utilized to uncover actionable insights from this data that can help predict outcomes related to sustainability initiatives such as emissions reductions. Spatial datasets can be visualized enabling us to better understand geographical patterns associated with certain environmental issues. Climate models are also employed in order to simulate how human activities influence global climates, enabling us to plan for future impacts such as sea level rise and extreme weather events.