• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.2
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• pp.325-331
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• 2017

Due to the climate change, natural disaster has been occurred more frequently and the number of snow disasters has been also increased. Therefore, many researches have been conducted to predict the amount of snow damages and to reduce snow damages. In this study, snow damages over last 21 years on the Natural Disaster Report were analyzed. As a result, Chungcheong-do, Jeolla-do, and Gangwon-do have the highest number of snow disasters. The multiple linear regression models were developed using the snow damage data of these three provinces. Daily fresh snow depth, daily maximum, minimum, and average temperatures, and relative humidity were considered as possible inputs for climate factors. Inputs for socio-economic factors were regional area, greenhouse area, farming population, and farming population over 60. Different regression models were developed based on the daily maximum snow depth. As results, the model efficiency considering all damage (including low snow depth) data was very low, however, the model only using the high snow depth (more than 25 cm) has more than 70% of fitness. It is because that, when the snow depth is high, the snow damage is mostly caused by the snow load itself. It is suggested that the 25 cm of snow depth could be used as the snow damage threshold based on this analysis.

• Journal of Korean Society of Forest Science
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• v.109 no.2
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• pp.202-210
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• 2020

This study investigated the optimal levels of stand density control considering the stability of Larix kaempferi stands. A stand density management diagram was developed from 259 sample plots. Based on these data, we determined an optimal level of the stand density control by identifying the relationship between the relative yield index (Ry) and height-to-diameter ratio. The estimated r-square (R²) of the stand density management diagram is 0.600. The analysis of the relationship between Ry and the slender tree incidence showed that when the stand density exceeded a certain threshold and the ratio of slender trees rapidly increased. The critical value of Ry was 0.63. The results of this study are expected to contribute to the establishment of stand management strategies that can reduce damage from natural causes, such as wind and snow, and to develop stand practice systems for the improved productivity of commercial forests.