Sung Yong Kim

Dr. Sung Yong Kim


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 August 2022 in Forests
Verified
Journal Article
Open access
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SKSung Yong Kim
Sung Yong Kim
Young-Jin LeeYoung-Jin Lee
Young-Jin Lee
JRJu-Yeol Ryu
Ju-Yeol Ryu
CKChun Geun Kwon
Chun Geun Kwon
KSKyung-Won Seo
Kyung-Won Seo
SKSung Yong Kim
Sung Yong Kim
A prediction model was developed for the wildfire fuel load of Korean red pine (Pinus densiflora) stands with susceptibility to forest fire based on the forest-growth model. Furthermore, a time-series analysis was performed on the variation in forest-fire fuel load according to forest management. National Forest Inventory stand data of 1434 plots for P. densiflora stands were used, and the final forest-fire fuel load prediction model was developed using the Weibull function and mortality model. The fit index of the diameter distribution model ranged from 0.58 (0th percentile) to 0.96 (50th percentile), and that of the mortality model was 0.68. The prediction of the stand growth variation after 20 years based on the growth data of managed and unmanaged stands indicated a mean stand density of 1518 trees per ha for unmanaged stands, and 885 trees per ha for managed stands. Regarding the variation in the available canopy fuel load distribution, the predicted annual increase was approximately 0.7 ton/ha for unmanaged stands and approximately 0.5 ton/ha for managed stands. These findings will contribute to setting fuel management criteria to prevent forest fire spread while providing the quantitative data of the characteristics of stand growth variation and the predicted wildfire fuel load.