[1]凌成星,刘华*,鞠洪波,等. 基于地面成像光谱数据特征的湿地典型植被类型识别研究——以东洞庭湖核心区湿地为例[J].西北林学院学报,2018,33(3):208-213.[doi:10.3969/j.issn.1001-7461.2018.03.32]
 LING Cheng-xing,LIU Hua*,JU Hong-bo,et al. Identifying Typical Wetland Vegetation Types Based on Imaging Spectrometer Data: A Case Study in Dongdongting Lake Wetland Area[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2018,33(3):208-213.[doi:10.3969/j.issn.1001-7461.2018.03.32]
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 基于地面成像光谱数据特征的湿地典型植被类型识别研究——以东洞庭湖核心区湿地为例()
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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:
208-213
栏目:
出版日期:
2018-05-31

文章信息/Info

Title:
 Identifying Typical Wetland Vegetation Types Based on Imaging Spectrometer Data: A Case Study in Dongdongting Lake Wetland Area
文章编号:
1001-7461(2018)03-0208-06
作者:
 凌成星1刘华1*鞠洪波1张怀清1孙华2由佳1李伟娜1
 (1.中国林业科学研究院 资源信息研究所,北京 100091;2.中南林业科技大学 林业遥感信息工程研究中心,湖南 长沙 410004)
Author(s):
 LING Cheng-xing1LIU Hua1*JU Hong-bo1ZHANG Huai-qing1SUN Hua2YOU Jia1LI Wei-na1
 (1.Institute of Forest Resource Information Techniques,CAF,Beijing 100091,China;2.Research Center of Forestry Remote Sensing & Information Engineering,Central South University Forestry & Technology,Changsha,Hunan 410004,China)
关键词:
 遥感成像高光谱数据光谱分析湿地植被植被类型识别
Keywords:
 remote sensing imaging spectrometer data dpectrum analysis wetland vegetation classification of wetland vegetation
分类号:
S771.8
DOI:
10.3969/j.issn.1001-7461.2018.03.32
文献标志码:
A
摘要:
 利用SOC710VP成像光谱仪在湖南省东洞庭湖区域湿地保护核心区获取了典型挺水植物芦苇、湿生植物苔草、泥蒿和栽培植物青菜的成像光谱数据,采用光谱微分技术的一阶导数分析方法和包络线去除方法分析了几种植被类型成像光谱曲线波段特性,提取成像光谱数据“双边”参数和吸收特征,并利用Fisher线性判别函数进行湿地植被类型识别,总分类精度达到87.39%,Kappa系数达到0.831 6。苔草分类后的精度最高,达到92.55%,青菜地的识别精度为92.31%,芦苇居中,识别精度达到86.11%,泥蒿的识别精度为80.65%。结果表明,地面采集的成像光谱数据进行分析得到的植被光谱特征变量具有较好的普适性和可靠性,可以为湿地植被类型的识别提供良好的科学依据。
Abstract:
 In order to accurately recognize the vegetation types,spectral information of typical wetland vegetation spectral data was collected by SOC710VP in the core region of the wetland reserve of east Dongting Lake,Hunan province.The first derivative analysis method and the envelope removal method were adopted to analyze the spectral characteristics of the vegetations in the region.By using Fisher linear discriminant function to identify wetland vegetation types,the total classification accuracy reached 88.59%,Kappa coefficient was 0.8247.The recognition accuracy for Carex was the highest (93.55%),followed by Brassica chinensis (92.31%),weeds (86.11%),and the recognition accuracy of Artemisia annua was low (80.65%).The results indicated that the spectral characteristics of the vegetation spectra obtained from the imaging spectral data had good universality and reliability,and it could provide a scientific basis for the identification of wetland vegetation.

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备注/Memo

备注/Memo:
 收稿日期:2017-07-06修回日期:2017-10-31
基金项目:中央级公益性科研院所基本科研业务费专项资金项目(IFRIT201505)。 
作者简介:凌成星,男,博士,助理研究员,研究方向:湿地资源遥感监测的理论和应用。E-mail:lingcx@ifrit.ac.cn
*通信作者:刘华,女,副研究员,硕士生导师,研究方向:森林与湿地资源遥感监测的应用。E-mail:liuhua@ifrit.ac.cn
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