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Model development to estimate site index values for six major tree species in North Korea

Journal of Forestry Research 2023年第2期34卷 387-400页

作者： Sohee Park A-Ram Yang Eun-hee Kim joongbin lim Division of Global Forestry Department of Future Forest StrategyNational Institute of Forest ScienceSeoul 02455Republic of Korea Forest ICT Research Center National Institute of Forest ScienceSeoul 02455Republic of Korea

Due to considerable deforestation in North Korea,there is a need to plan forest restoration programs based on scientific forest *** this study,a methodology was developed for estimating the site index values of six major tree species and the forest productivity *** site index values of these tree species were derived in South Korea using the Chapman-Richards *** values were used with data from the 6th National Forest Inventory,which included 20 types of edaphic,topographic,and climatic factors,and random forest analysis—a widely used machine learning technique for spatial prediction—to develop a new model for estimating the site index values of these species across South *** prediction accuracy of this model was evaluated using the root mean square *** results show that the prediction accuracy was high,with a root mean square error of~***,the importance of the variables related to climate and geography was generally *** proposed site index estimation model for six tree species was applied across North Korea,and its effectiveness tested by comparing the estimated values with those reported in literature from North *** differences between the model outputs and recorded data in the northern alpine regions were presumably due to the lack of data for high-altitude regions in South *** model is based on the determination of the suitability of tree species in restoration ***,it can contribute to the evaluation of forest productivity in North Korea and may help plan efficient forest restoration programs.

关键词： Environmental factors Forest productivity Machine learning North Korea Random forest Site index

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