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

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-h...
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Autor*in:	Xun Zhu [verfasserIn] Timothy J. Pasch [verfasserIn] Mohamed Aymane Ahajjam [verfasserIn] Aaron Bergstrom [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	arctic topic modeling network analysis arctic resiliency sustainable development permafrost

Übergeordnetes Werk:	In: Sustainability - MDPI AG, 2009, 14(2022), 24, p 16493
Übergeordnetes Werk:	volume:14 ; year:2022 ; number:24, p 16493

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/su142416493

Katalog-ID:	DOAJ082973121

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author	Xun Zhu
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title	Environmental Monitoring for Arctic Resiliency and Sustainability: An Integrated Approach with Topic Modeling and Network Analysis
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title_sort	environmental monitoring for arctic resiliency and sustainability: an integrated approach with topic modeling and network analysis
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title_auth	Environmental Monitoring for Arctic Resiliency and Sustainability: An Integrated Approach with Topic Modeling and Network Analysis
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.
abstractGer	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.
abstract_unstemmed	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.
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Environmental Monitoring for Arctic Resiliency and Sustainability: An Integrated Approach with Topic Modeling and Network Analysis

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