Data Science and Human-Environment Systems

The first comprehensive treatment of data science as a new and powerful way to understand and manage human-environment interactions.

Steven M. Manson (Author)

9781108486286, Cambridge University Press

Hardback, published 9 February 2023

300 pages
25 x 17.5 x 2.1 cm, 0.66 kg

'In a rapidly changing landscape, I've found this to be an authoritative book that frames the challenges that human-environment systems face and the solutions that data science could provide. I was struck by how the book's complex ideas are framed and communicated, making it not only accessible and suitable for those new to the field, but also mandatory reading for those who are experienced and looking for a cutting-edge perspective. Intelligently written and highly relevant, this book successfully bridges the gap between data science and human-environment systems.' Alison Heppenstall, University of Glasgow

Transformation of the Earth's social and ecological systems is occurring at a rate and magnitude unparalleled in human experience. Data science is a revolutionary new way to understand human-environment relationships at the heart of pressing challenges like climate change and sustainable development. However, data science faces serious shortcomings when it comes to human-environment research. There are challenges with social and environmental data, the methods that manipulate and analyze the information, and the theory underlying the data science itself; as well as significant legal, ethical and policy concerns. This timely book offers a comprehensive, balanced, and accessible account of the promise and problems of this work in terms of data, methods, theory, and policy. It demonstrates the need for data scientists to work with human-environment scholars to tackle pressing real-world problems, making it ideal for researchers and graduate students in Earth and environmental science, data science and the environmental social sciences.

1. Data Science and Human-Environment Systems
2. Data Gaps and Potential
3. Big Methods, Big Messes, Big Solutions
4. Theory and the Perils of Black Box Science
5. Policy Dilemmas
6. Ways Forward for the Data Science of Human-Environment Systems
References
Index.

Subject Areas: Environmental science, engineering & technology [TQ], Conservation of the environment [RNK], The environment [RN], Environment law [LNKJ], Environmental economics [KCN]