[1]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.[doi:10.3969/j.issn.1001-7461.2018.03.31]
 CHEN Hong-bing,HUANG Bei-bei,PENG Dao-li*. Comparison of Pixel Decomposition Models for the Estimation of Fractional Vegetation Coverage[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2018,33(3):203-207.[doi:10.3969/j.issn.1001-7461.2018.03.31]
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 基于混合像元分解的植被覆盖度模型比较研究()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第33卷
期数:
2018年第3期
页码:
203-207
栏目:
出版日期:
2018-05-31

文章信息/Info

Title:
 Comparison of Pixel Decomposition Models for the Estimation of Fractional Vegetation Coverage
文章编号:
1001-7461(2018)03-0203-05
作者:
 陈虹兵1黄贝贝2彭道黎1*
 (1.北京林业大学,北京 100083;2.四川省林业调查规划院,四川 成都 610036)
Author(s):
 CHEN Hong-bing1HUANG Bei-bei2PENG Dao-li1*
 (1.Beijing Forestry University,Beijing 100083,China; 2.Sichuan Forestry Survey and Planning Institute,Chengdu,Sichuan 610036,China)
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
Keywords:
 fractional vegetation cover mixed-pixel unmixing dimidiate pixel model linear spectral mixture model
分类号:
S718.5
DOI:
10.3969/j.issn.1001-7461.2018.03.31
文献标志码:
A
摘要:
 准确地估算植被覆盖度是生态学及全球植被覆盖变化研究的重要内容。应用遥感技术估测植被覆盖度成为近年来研究的热点之一,但影像混合像元的存在成为制约植被覆盖度提取精度的难题之一。以延庆区2014年的Landsat8 OLI影像为数据源,结合二类调查及补充调查数据,采用像元二分模型法和线性光谱混合模型法对提取植被覆盖度,对比分析2种模型的适用性。结果表明,基于像元二分模型法的植被覆盖度提取精度达到85.31%,基于线性光谱混合模型的植被覆盖度提取精度达到88.76%,线性光谱混合模型的提取效果要好于像元二分模型法,最后生成了延庆区植被覆盖分布图,可为县域尺度应用Landsat8 OLI影像估测植被覆盖度提供参考。
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.

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备注/Memo

备注/Memo:
 收稿日期:2017-07-10修回日期:2017-10-18
基金项目:国家重点林业监测技术示范推广项目(2015-02)。
作者简介:陈虹兵,男,硕士研究生,研究方向:森林资源监测与评价。E-mail:626649554@qq.com
*通信作者:彭道黎,男,教授,博士,研究方向:森林资源监测与评价。E-mail:dlpeng@bjfu.edu.cn
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