论文部分内容阅读
用望高法测定箭杆杨和小叶杨立木材积,结果总平均误差箭杆杨为-2.50％,小叶杨为-5.45％,表明其精度是高的。从样本资料看出,多数出现负误差,其原因笔者认为是由于形和公式本身所引起。 望高和胸径密切相关,可以建立回归方程。经拟合计算,其最佳回归方程式为 logH_R=a+b[1/D_(1.3)] 将望高与胸径的经验回归方程式代入望高计算法,从而得出材积计算式: 箭杆杨 V=(π/60000)D_(1.3)~2[_(10)(1.08257407-2.189859543(1/D(1.3))+(1.2/2)] 小叶杨 V=(π/60000)D_(1.3)~2[_(10)(1.165505188-4.060596389(1/D(1.3))+(1.3/2)]
The results showed that the total mean error was -2.50% for arrowhead poplar and -5.45% for Populus simonii, which showed that the precision was high. From the sample data shows that most of the negative error occurs, the reason I think that is due to the shape and formula itself caused. Height and DBH are closely related to the regression equation can be established. After fitting, the best regression equation is logH_R = a + b [1 / D_ (1.3)]. The empirical regression equation of height-height and diameter at breast height is substituted into the height-elevation calculation method, = (π / 60000) D_ (1.3) ~ 2 [_ (10) (1.08257407-2.189859543 (1 / D (1.3)) + (1.2 / 2) 2 [_ (10) (1.165505188-4.060596389 (1 / D (1.3)) + (1.3 / 2)]