Climate Change Adaptation: Difference between revisions
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''This page is about the intersection of climate change adaptation and machine learning. For an overview of climate change adaptation as a whole, please see the [https://en.wikipedia.org/wiki/Climate_change_adaptation Wikipedia page] on this topic.''[[File:Societal-adaptation.png|thumb|A summary of the different domains within which machine learning can support climate adaptation. Figure from "Tackling Climate Change with Machine Learning."]]
Climate change adaptation refers to changes that can increase the resilience and robustness of earth and social systems. A system is resilient if it can gracefully recover from climate impacts, and it is robust if it has the impacts themselves are minimal.
Three ways that machine learning can support adaptation are highlighted in the paper "Tackling Climate Change with Machine Learning,"<blockquote>
* Sounding alarms: Identifying and prioritizing the areas of highest risk, by using evidence of risk from historical data.
* Providing annotation: Extracting actionable information or labels from unstructured raw data.
* Promoting exchange: Making it easier to share resources and information to pool and reduce risk.
</blockquote>
== Machine Learning Application Areas ==
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