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Data Science for Nature and Sustainability

Many key sustainability issues translate into decision and optimization problems and could greatly benefit from data-driven decision making tools. In fact, the impact of modern information technology has been highly uneven, mainly benefiting large firms in profitable sectors, with little or no benefit in terms of the environment. Our vision is that data-driven methods can — and should — play a key role in increasing the efficiency and effectiveness of the way we manage and allocate our natural resources.

A particularly exciting aspect of this domain is that traditional measures for many aspects of nature and sustainability are very poor or nonexistent, since they tend to involve non-monetized outcomes or activities in very poor regions without much market activity (e.g. subsistence crop production). Thus, an ability to reliably extract useful information from images, videos, and text without human intervention will create unprecedented opportunities for new insights and better decisions.

Contributors

Stefano Ermon
Computer Science
David Lobell
Earth System Science
Margot Gerritsen
Energy Resources Engineering