高光谱Hyperion与高分辨率WorldView-2卫星数据协同下的岩性分类
发布时间：2018-07-16 22:55
【摘要】：在目前的技术条件下,一种遥感数据源很难同时具有高空间分辨率和高光谱分辨率特征,因此如何协同使用不同来源的遥感数据进行矿物岩石识别就成了遥感地质领域的重要研究内容之一。本文结合高空间分辨率WorldView-2数据和高光谱分辨率Hyperion数据,以新疆乌恰县矿物岩石识别与地层划分为例探讨多源遥感数据协同的岩性分类。通过对比2种数据源的空间和光谱探测能力,找到其协同基础。借鉴传统的同源数据融合方法,把World View-2多光谱数据降采样到不同空间尺度,并进行主成分变换,采用第一主成分与Hyperion融合产生协同数据。基于SAM光谱角分类法,分别采用WorldView-2多光谱原始数据、Hyperion原始数据和各协同数据对研究区的岩性进行自动分类。结果表明,各协同数据岩性分类精度较高,Hyperion次之,WorldView-2数据岩性分类精度最低。
[Abstract]:Under the current technological conditions, it is difficult for a remote sensing data source to have both high spatial resolution and hyperspectral resolution. Therefore, how to use remote sensing data from different sources to identify minerals and rocks has become one of the important research contents in the field of remote sensing geology. Combined with high spatial resolution WorldView-2 data and hyperspectral resolution Hyperion data, this paper discusses the lithologic classification of multi-source remote sensing data by taking the recognition and stratigraphic classification of minerals and rocks in Wuqian County, Xinjiang as an example. By comparing the spatial and spectral detection capabilities of the two data sources, the cooperative basis of the two data sources is found. Based on the traditional homologous data fusion method, the World View-2 multispectral data is down-sampled to different spatial scales, and principal component transformation is carried out. The first principal component and Hyperion fusion are used to produce cooperative data. Based on the SAM spectral angle classification method, the lithology of the study area was automatically classified by the WorldView-2 multispectral original data, Hyperion raw data and various cooperative data, respectively. The results show that the lithologic classification accuracy of all synergetic data is higher than that of Hyperion and WorldView-2 data is the lowest.
【作者单位】： 中国地质大学信息工程学院;山东女子学院;成都理工大学国土资源部地学空间信息技术重点实验室;中国地质大学公共管理学院;国家测绘地理信息局四川基础地理信息中心;
【基金】：国家自然科学基金项目(41702358,41771444,41201440) 四川省教育厅重点项目(16ZA0090,15ZA0078) 中国地质调查局地调项目(2017120) 山东高等学校科技计划项目(J15LN11)
【分类号】：P627
[Abstract]:Under the current technological conditions, it is difficult for a remote sensing data source to have both high spatial resolution and hyperspectral resolution. Therefore, how to use remote sensing data from different sources to identify minerals and rocks has become one of the important research contents in the field of remote sensing geology. Combined with high spatial resolution WorldView-2 data and hyperspectral resolution Hyperion data, this paper discusses the lithologic classification of multi-source remote sensing data by taking the recognition and stratigraphic classification of minerals and rocks in Wuqian County, Xinjiang as an example. By comparing the spatial and spectral detection capabilities of the two data sources, the cooperative basis of the two data sources is found. Based on the traditional homologous data fusion method, the World View-2 multispectral data is down-sampled to different spatial scales, and principal component transformation is carried out. The first principal component and Hyperion fusion are used to produce cooperative data. Based on the SAM spectral angle classification method, the lithology of the study area was automatically classified by the WorldView-2 multispectral original data, Hyperion raw data and various cooperative data, respectively. The results show that the lithologic classification accuracy of all synergetic data is higher than that of Hyperion and WorldView-2 data is the lowest.
【作者单位】： 中国地质大学信息工程学院;山东女子学院;成都理工大学国土资源部地学空间信息技术重点实验室;中国地质大学公共管理学院;国家测绘地理信息局四川基础地理信息中心;
【基金】：国家自然科学基金项目(41702358,41771444,41201440) 四川省教育厅重点项目(16ZA0090,15ZA0078) 中国地质调查局地调项目(2017120) 山东高等学校科技计划项目(J15LN11)
【分类号】：P627
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