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http://dx.doi.org/10.7780/kjrs.2021.37.6.2.9

A Study on the Research Topics and Trends in Korean Journal of Remote Sensing: Focusing on Natural & Environmental Disasters  

Kim, Taeyong (Division of Earth Environmental System Sciences (Major of Earth Environmental Sciences), Pukyong National University)
Park, Hyemin (Division of Earth Environmental System Sciences (Major of Earth Environmental Sciences), Pukyong National University)
Heo, Junyong (Division of Earth Environmental System Sciences (Major of Earth Environmental Sciences), Pukyong National University)
Yang, Minjune (Department of Earth and Environmental Sciences, Pukyong National University)
Publication Information
Korean Journal of Remote Sensing / v.37, no.6_2, 2021 , pp. 1869-1880 More about this Journal
Abstract
Korean Journal of Remote Sensing (KJRS), leading the field of remote sensing and GIS in South Korea for over 37 years, has published interdisciplinary research papers. In this study, we performed the topic modeling based on Latent Dirichlet Allocation (LDA), a probabilistic generative model, to identify the research topics and trends using 1) the whole articles, and 2) specific articles related to natural and environmental disasters published in KJRS by analyzing titles, keywords, and abstracts. The results of LDA showed that 4 topics('Polar', 'Hydrosphere', 'Geosphere', and 'Atmosphere') were identified in the whole articles and the topic of 'Polar' was dominant among them (linear slope=3.51 × 10-3, p<0.05) over time. For the specific articles related to natural and environmental disasters, the optimal number of topics were 7 ('Marine pollution', 'Air pollution', 'Volcano', 'Wildfire', 'Flood', 'Drought', and 'Heavy rain') and the topic of 'Air pollution' was dominant (linear slope=2.61 × 10-3, p<0.05) over time. The results from this study provide the history and insight into natural and environmental disasters in KRJS with multidisciplinary researchers.
Keywords
Topic modeling; Latent Dirichlet Allocation; Natural and Environmental disasters; Trend analysis; Korean Journal of Remote Sensing;
Citations & Related Records
Times Cited By KSCI : 30  (Citation Analysis)
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