Environmental data science: Part 2

Abstract

Environmental data science is a multi-disciplinary and mature field of research at the interface of statistics, machine learning, information technology, climate and environmental science. The two-part special issue 'Environmental Data Science' comprises a set of research articles and opinion pieces led by statisticians who are at the forefront of the field. This editorial identifies and discusses common research themes that appear in the contributions to Part 2, which focuses on applications. These include spatio-temporal modeling; the problem of aggregation and sparse sampling; the importance of community-building and training for the next generation of specialists in environmental data science; and the need to look forward at the challenges that lie ahead for the discipline. This editorial complements that of Part 1, which largely focuses on statistical methodology; see Zammit-Mangion, Newlands, and Burr (2023).

Environmental data science: Part 1

“…We would also like to thank all the reviewers (more than 35 on our last count) without whom this issue would not have been possible. The response we had to the special issue was overwhelmingly positive, so much so that the contributions are organized into two parts (with the second discussed by Burr et al 2022); we thank the broader environmetrics community for their support in making this special issue a reality. Andrew Zammit‐Mangion also acknowledges the support of the Australian Research Council Discovery Early Career Researcher Award DE180100203; Wesley S. Burr acknowledges the support of the (Canadian) National Science and Engineering Research Council Discovery Grant DG‐2017‐04741; and Nathaniel K. Newlands acknowledges the support of the Canadian Agricultural Partnership (CAP) Program, Agriculture and Agri‐Food Canada.…”

“…This editorial focuses on the core research strands of the contributions to Part 1 of the special issue. Part 2 of the special issue comprises an additional eight research articles and four opinion pieces, which we discuss in a separate editorial; see Burr et al (2022).…”