Environmental Monitoring for Arctic Resiliency and Sustainability: An Integrated Approach with Topic Modeling and Network Analysis

Xun Zhu (), Timothy J. Pasch (), Mohamed Aymane Ahajjam and Aaron Bergstrom
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Xun Zhu: Department of Communication, College of Arts & Sciences, University of North Dakota, Grand Forks, ND 58202, USA
Timothy J. Pasch: Department of Communication, College of Arts & Sciences, University of North Dakota, Grand Forks, ND 58202, USA
Mohamed Aymane Ahajjam: School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND 58202, USA
Aaron Bergstrom: Computational Research Center, University of North Dakota, Grand Forks, ND 58202, USA

Sustainability, 2022, vol. 14, issue 24, 1-20

Abstract: The Arctic environment is experiencing profound and rapid changes that will have far-reaching implications for resilient and sustainable development at the local and global levels. To achieve sustainable Arctic futures, it is critical to equip policymakers and global and regional stake- and rights-holders with knowledge and data regarding the ongoing changes in the Arctic environment. Community monitoring is an important source of environmental data in the Arctic but this research argues that community-generated data are under-utilized in the literature. A key challenge to leveraging community-based Arctic environmental monitoring is that it often takes the form of large, unstructured data consisting of field documents, media reports, and transcripts of oral histories. In this study, we integrated two computational approaches—topic modeling and network analysis—to identify environmental changes and their implications for resilience and sustainability in the Arctic. Using data from community monitoring reports of unusual environmental events in the Arctic that span a decade, we identified clusters of environmental challenges: permafrost thawing, infrastructure degradation, animal populations, and fluctuations in energy supply, among others. Leveraging visualization and analytical techniques from network science, we further identified the evolution of environmental challenges over time and contributing factors to the interconnections between these challenges. The study concludes by discussing practical and methodological contributions to Arctic resiliency and sustainability.

Keywords: arctic; topic modeling; network analysis; arctic resiliency; sustainable development; permafrost; degrading infrastructure; arctic data visualization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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