北京林业大学学报2017，Vol.39Issue(12)：36-43,8.DOI:10.13332/j.1000-1522.20170260
基于随机森林的杉木适生性预测研究
Prediction of adaptability of Cunninghamia lanceolata based on random forest
摘要
Abstract
In this paper, Cunninghamia lanceolata was taken as research object in the Experimental Center of Tropical Forestry of Chinese Academy of Forestry, Pingxiang County of Guangxi Province of southern China, we selected the sub-compartments with dominant species of Cunninghamia lanceolata, divided the experimental data into training samples and test samples at 7:3 ratio and established a random forest model with altitude, physiognomy type, slope degree, slope aspect, slope position, soil type, parent rock, soil thickness, humus layer thickness as input variables and growth adaptability of Cunninghamia lanceolata as output variable to predict its adaptability for afforestation sites. At the same time, we analyzed the weight of main site factors on the growth of Cunninghamia lanceolata using the established model. This study showed that the training accuracy of adaptability of Cunninghamia lanceolata based on random forest model was 84. 3% and the generalization accuracy reached 89. 5%. Site factors greatly affecting the growth of Cunninghamia lanceolata were slope degree, slope aspect, the humus layer thickness and altitude, while soil type and soil thickness less affected the growth of Cunninghamia lanceolata. In terms of single site factor, the slopes ranged from 25° to 34° and the altitude greater than 350 m were more suitable for the growth of Cunninghamia lanceolata. The established model based on random forest could deal with complex nonlinear relations and could be applied to make afforestation decision to non-forest lands, then to realize the organic unification of the suitability judgment of Cunninghamia lanceolata with forest land and non-forest land, and the model can be extended to other tree species and provide theoretical support to the problem of matching species with site.关键词
适地适树/随机森林/杉木/适生性Key words
matching species with site/random forest/Cunninghamia lanceolata/adaptability分类
农业科技引用本文复制引用
高若楠,苏喜友,谢阳生,雷相东,陆元昌..基于随机森林的杉木适生性预测研究[J].北京林业大学学报,2017,39(12):36-43,8.基金项目
中央级公益性科研院所基本科研业务费专项(IFRIT201501)、林业公益性行业科研专项(201504303). （IFRIT201501）
