福建师范大学学报（自然科学版）2011，Vol.27Issue(2)：124-132,9.
基于改进型B-P神经网络的西天山云杉林生物量估算
Picea Schrenkiana Forest Biomass Estimate in the West Tianshan Mountain Based on Improved B-P Neural Network
摘要
Abstract
It takes Picea schrenkiana as an example. With the application of B-P artificial neural network technology, using seven kinds of vegetation index such as NDVI and the former five PCAs that come from TM/ETM principal component transform, a neural network model was established based on the data of remote sensing and field measurements in Nileke west of the Tianshan Mountains. After training and simulation,compared this model with the field measurements, the result shows that its average relative error between estimating value and actual value is 8.21％, which proved to be higher accuracy.关键词
B-P神经网络/天山云杉林/生物量/遥感植被指数Key words
B-P neural network/ Picea schrenkiana/ forest biomass/ plant index of remote sensing分类
农业科技引用本文复制引用
袁野,李虎,刘玉峰..基于改进型B-P神经网络的西天山云杉林生物量估算[J].福建师范大学学报（自然科学版）,2011,27(2):124-132,9.基金项目
国家基础科学人才培养基金资助(J0830521) （J0830521）
