基于遥感、地理信息系统和人工神经网络的呼中林区森林蓄积量估测

Estimation of forest volume in Huzhong forest area based on RS,GIS and ANN

利用遥感图像光谱信息良好的综合性和现势性以及地理信息系统(GIS)强大的空间分析功能,结合人工神经网络(ANN)可优化求解非线性复杂系统的功能,对呼中林区森林蓄积量进行了估测.结果表明:中红外波段与森林蓄积量间存在明显的负相关关系,说明中红外波段对估测森林蓄积量具有一定潜力;可见光波段和光谱变换第一主成分与森林蓄积量间也存在负相关关系;地形因子中海拔对研究区森林蓄积量的影响最大,坡度和坡向对蓄积量的影响较小.基于最佳的ANN网络参数、适当的GIS提取信息和遥感波段,呼中林区森林蓄积量的预测值和实测值的相关系数达0.973,经主成分变换后,数据量被有效降低,而预测精度只有少量下降(R2=0.934).

Based on remote sensing （RS） which has integrated and realistic characteristics, geographic information system （GIS） which has powerful spatial analysis ability, and artificial neutral network （ANN） which can optimize nonlinear complex systems, the forest volume in Huzhong forest area was estimated. The results showed that there was an obvious negative correlation between the forest volume and infrared band, indicating that infrared band had definite potential in estimating forest volume. The forest volume also negatively correlated with visible band and PCl. Among the topographic factors, altitude exerted more influence than aspect and slope on the estimation of forest volume. The correlation coefficient of predicted value and actual value reached to 0. 973, when the optimal ANN parameter, suitable GIS information, and RS bands were adopted. After principal component transformation, the amount of observation data was effectively reduced, while the predicted precision only had a small decline （R2 = 0. 934）.