应用生态学报2012，Vol.23Issue(9)：2422-2428,7.
毛竹林地上部分生物量遥感估算模型的可移植性
Transferability of remote sensing-based models for estimating moso bamboo forest aboveground biomass
摘要
Abstract
Taking the moso bamboo production areas Lin ' an, Anji, and Longquan in Zhejiang Province of East China as study areas, and based on the integration of field survey data and Landsat 5 Thematic Mappr images, five models for estimating the moso bamboo (Phyllostachys heterocycla var. pubescens) forest biomass were constructed by using linear, nonlinear, stepwise regression, multiple regression, and Erf-BP neural network, and the models were evaluated. The models with higher precision were then transferred to the study areas for examining the model' s transferability. The results indicated that for the three moso bamboo production areas, Erf-BP neural network model presented the highest precision, followed by stepwise regression and nonlinear models. The Erf-BP neural network model had the best transferability. Model type and independent variables had relatively high effects on the transferability of statistical-based models.关键词
地上生物量/遥感估算模型/移植性/毛竹Key words
aboveground biomass/remote sensing-based model/transferability/moso bamboo分类
农业科技引用本文复制引用
余朝林,杜华强,周国模,徐小军,桂祖云..毛竹林地上部分生物量遥感估算模型的可移植性[J].应用生态学报,2012,23(9):2422-2428,7.基金项目
浙江省自然科学基金项目(Y3100427)、国家自然科学基金项目(31070564)、科技部"973"项目(2011CB302705)、浙江省重点科技创新团队项目(2012R10030-01)和国家林业局948项目(2008-4-49)资助. （Y3100427）
