| 利用Sentinel-2A多光谱成像仪与Landsat8陆地成像仪影像进行普陀山岛植被分类效果比较 |
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| 引用本文： | 章晓洁,邓艳芬,张亚超,蒋芸芸,邱桔斐.利用Sentinel-2A多光谱成像仪与Landsat8陆地成像仪影像进行普陀山岛植被分类效果比较[J].测绘通报,2019,0(10):97-100. |
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| 作者姓名： | 章晓洁 邓艳芬 张亚超 蒋芸芸 邱桔斐 |
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| 作者单位： | 国家海洋局东海海洋环境调查勘察中心,上海,200137;国家海洋局东海海洋环境调查勘察中心,上海,200137;国家海洋局东海海洋环境调查勘察中心,上海,200137;国家海洋局东海海洋环境调查勘察中心,上海,200137;国家海洋局东海海洋环境调查勘察中心,上海,200137 |
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| 基金项目： | 海洋公益性行业科研专项（201505009）；国家海洋局东海分局青年科技基金（201609） |
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| 摘 要： | 卫星遥感技术可用于海岛资源调查。Sentinel-2A与Landsat 8两颗卫星都可免费提供空间分辨率较高的多光谱遥感影像，在海岛调查中的应用潜力较大。本文以浙江舟山普陀山岛为例开展了针对这两种影像在海岛植被分类中的应用效果的研究，分别利用Sentinel-2A多光谱成像仪（MSI）和Landsat 8陆地成像仪（OLI）影像基于最大似然法分类获得了该岛阔叶林、针阔混交林、针叶林、灌丛、草丛等植被及其他地物的分布情况，并进行了精度检验，结果表明MSI的总体分类精度略高于OLI。
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| 关 键 词： | Sentinel-2A Landsat8 遥感植被分类 最大似然法 总体分类精度 |
| 收稿时间： | 2019-02-01 |
Comparison of vegetation classification performances on Putuoshan island using Sentinel-2A MSI and Landsat 8 OLI images |
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| ZHANG Xiaojie,DENG Yanfen,ZHANG Yachao,JIANG Yunyun,QIU Jufei.Comparison of vegetation classification performances on Putuoshan island using Sentinel-2A MSI and Landsat 8 OLI images[J].Bulletin of Surveying and Mapping,2019,0(10):97-100. |
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| Authors: | ZHANG Xiaojie DENG Yanfen ZHANG Yachao JIANG Yunyun QIU Jufei |
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| Institution: | East Sea Marine Environmantal Investigating & Surveying Center, SOA China, Shanghai 200137, China |
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| Abstract: | Satellite remote sensing technique can be used to investigate resources of sea-islands. Both Sentinel-2A and Landsat 8 satellites freely provide multi-spectral remote sensing images with relatively high spatial resolution which means high potential of sea-island investigation. Taking Putuoshan island, Zhoushan, Zhejiang as example, vegetation classifications on sea-island using images of these two satellites are compared. Based on maximum likelihood classification method, classes of broad-leaved forest, coniferous and broad-leaved mixed forest, coniferous forest, shrub, grassland and other land uses are extracted respectively using Sentinel-2A MSI and Landsat 8 OLI images. And accuracy validation results show that the overall classification accuracy of MSI is a little higher than that of OLI. |
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| Keywords: | Sentinel-2A Landsat 8 remote sensing vegetation classification maximum likelihood overall classification accuracy |
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