摘要
遥感图像光谱信息具有良好的综合性和现势性,利用遥感信息和GIS技术进行森林生物量估算及碳过程的研究已经成为一种全新的手段。本文对森林生物量遥感估算方法及其应用进行了深入分析,总结了利用遥感信息进行森林生物量估算的四种主要方法:遥感信息参数与生物量拟合关系的方法、遥感数据与过程模型融合的方法、基准样地法(KNN方法)以及人工神经网络模型方法,并在此基础上分析了当前该领域研究的不足,以及今后利用遥感方法进行森林生物量估算的主要发展方向。
The spectral information of remote sensing images has integrated and realistic characteristics. It has become an important means of using remote sensing information and GIS technology to estimate forest biomass in global change research area. Firstly, the development of using remote sensing information to estimate forest biomass was summarized in this paper. Then four methods which included the method based on relationship between remote sensing information and biomass, the method based on fusion remote sensing data and process model, the method based on K-Nearest neighbor and the method based on artificial neural network were discussed. Finally the shortcomings of current research and the emphases of future research were given in this paper.
出处
《地球信息科学》
CSCD
2006年第4期122-128,共7页
Geo-information Science
基金
国家重点基础研究计划(G2002CB412507)
中国科学院百人计划项目
中国博士后科学基金资助项目
王宽诚教育基金会资助项目.
关键词
森林生物量
遥感信息
模型
KNN
人工神经网络
forest biomass
remote sensing information
model
KNN
artificial neural network
