西北林学院学报2018，Vol.33Issue(3)：203-207,265,6.DOI:10.3969/j.issn.1001-7461.2018.03.31
基于混合像元分解的植被覆盖度模型比较研究
Comparison of Pixel Decomposition Models for the Estimation of Fractional Vegetation Coverage
摘要
Abstract
Accurate estimation of vegetation coverage is an important part for the study of ecology and global vegetation coverage change.The application of remote sensing technology to estimate vegetation coverage has become one of the hot spots in recent years.However,the presence of mixed pixels is one of the problems that restricts the accuracy of vegetation coverage.Taking the images of Landsat8 OLI of Yanqing County in 2014 as datum resources,combined with the data of the second class forestry inventory as well as supplementary inventory data,the vegetation coverages were extracted by using pixel dichotomy and linear spectral mixture model.The applicability of two kinds of models was compared.The results showed that dimidiate pixel model of vegetation coverage based on extraction accuracy reached 85.31％,linear spectral mixture model of vegetation coverage based on extraction accuracy was 88.76％,the extraction effect of linear spectral mixture model was better than the dimidiate pixel model.The distribution map of Yanqing vegetation coverage was finally generated to provide a reference for estimating vegetation coverage using Landsat8 OLI images at county scale.关键词
植被覆盖度/混合像元分解/像元二分模型/线性光谱混合模型Key words
fractional vegetation cover/mixed-pixel unmixing/dimidiate pixel model/linear spectral mixture model分类
农业科技引用本文复制引用
陈虹兵,黄贝贝,彭道黎..基于混合像元分解的植被覆盖度模型比较研究[J].西北林学院学报,2018,33(3):203-207,265,6.基金项目
国家重点林业监测技术示范推广项目(2015-02). （2015-02）
