文献类型：期刊文献

中文题名：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

英文题名：Identifying Typical Wetland Vegetation Types Based on Imaging Spectrometer Data:A Case Study in Dongdongting Lake Wetland Area

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]

第一作者：凌成星

机构：[1]中国林业科学研究院资源信息研究所;[2]中南林业科技大学林业遥感信息工程研究中心

年份：2018

卷号：33

期号：3

起止页码：208-213

中文期刊名：西北林学院学报

外文期刊名：Journal of Northwest Forestry University

收录：CSTPCD;;北大核心:【北大核心2017】；CSCD:【CSCD_E2017_2018】；

基金：中央级公益性科研院所基本科研业务费专项资金项目(IFRIT201505)

语种：中文

中文关键词：遥感;成像高光谱数据;光谱分析;湿地植被;植被类型识别

外文关键词：remote sensing;imaging spectrometer data;dpectrum analysis;wetland vegetation;classification of wetland vegetation

分类号：S771.8

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。
In order to accurately recognize the vegetation types,spectral information of typical wetland vegetation spectral data was collected by SOC710 VP 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.