Internet Explorer 11 is being discontinued by Microsoft in August 2021.
If you have difficulties viewing the site on Internet Explorer 11 we
recommend using a different browser such as Microsoft Edge, Google
Chrome, Apple Safari or Mozilla Firefox.
Last updated 10th July 2024: Online ordering is currently unavailable due to technical issues. We apologise for any delays responding to customers while we resolve this. For further updates please visit our website https://www.cambridge.org/news-and-insights/technical-incident
Data Science for the Geosciences provides students and instructors with the statistical and machine learning foundations to address Earth science questions using real-world case studies in natural hazards, climate change, environmental contamination and Earth resources. It focuses on techniques that address common characteristics of geoscientific data, including extremes, multivariate, compositional, geospatial and space-time methods. Step-by-step instructions are provided, enabling readers to easily follow the protocols for each method, solve their geoscientific problems and make interpretations. With an emphasis on intuitive…
If you believe you should have access to this content, please contact
your institutional librarian or consult our
FAQ page
for further information about accessing our content.
Also available to purchase from these educational ebook suppliers
Authors
Lijing Wang,Stanford University, California
Dr. Lijing Wang is a Postdoctoral Research Fellow in the Earth and Environmental Sciences Area at Lawrence Berkeley National Laboratory. She earned her Ph.D. from the Department of Earth and Planetary Sciences at Stanford University. Her research centers on integrating geoscientific data, such as geophysical surveys and in-situ hydrological measurements, with hydrological modeling to develop informed solutions for water resource management. She was a Stanford Data Science Scholar and had been a teaching assistant for the Data Science for Geosciences course at Stanford for over three years. She has received the Harriet Benson Fellowship from Stanford for her exceptional research accomplishments.
David Zhen Yin,Stanford University, California
Dr. Zhen Yin is a research scientist and co-founder of the Stanford Mineral-X (https://mineralx.stanford.edu/) at Stanford Doerr School of Sustainability. His research developments in data science have been implemented in various subjects, including Antarctica topographic modeling, critical mineral explorations in Asia/North America/Africa, and North Sea projects. He was previously a Research Associate at the Edinburgh Time-Lapse Project in Scotland, leading a research collaboration with Equinor from 2016 to 2018, and a Postdoctoral Fellow at the Stanford Chevron Center of Research Excellence from 2018 to 2021.
Jef Caers,Stanford University, California
Dr. Jef Caers is Professor of Earth and Planetary Sciences in the Stanford Doerr School of Sustainability. He is the author of a wide range of journal papers across mathematics, statistics, geological sciences, geophysics, engineering and computer science, and four other books. He has received several best paper awards, as well as the 2001 Vistelius Award from the International Association for Mathematical Geosciences (IAMG) and the 2014 Krumbein Medal from the IAMG for his career achievement.