【摘要】：在目前的技術(shù)條件下,一種遙感數(shù)據(jù)源很難同時(shí)具有高空間分辨率和高光譜分辨率特征,因此如何協(xié)同使用不同來源的遙感數(shù)據(jù)進(jìn)行礦物巖石識別就成了遙感地質(zhì)領(lǐng)域的重要研究內(nèi)容之一。本文結(jié)合高空間分辨率WorldView-2數(shù)據(jù)和高光譜分辨率Hyperion數(shù)據(jù),以新疆烏恰縣礦物巖石識別與地層劃分為例探討多源遙感數(shù)據(jù)協(xié)同的巖性分類。通過對比2種數(shù)據(jù)源的空間和光譜探測能力,找到其協(xié)同基礎(chǔ)。借鑒傳統(tǒng)的同源數(shù)據(jù)融合方法,把World View-2多光譜數(shù)據(jù)降采樣到不同空間尺度,并進(jìn)行主成分變換,采用第一主成分與Hyperion融合產(chǎn)生協(xié)同數(shù)據(jù)。基于SAM光譜角分類法,分別采用WorldView-2多光譜原始數(shù)據(jù)、Hyperion原始數(shù)據(jù)和各協(xié)同數(shù)據(jù)對研究區(qū)的巖性進(jìn)行自動(dòng)分類。結(jié)果表明,各協(xié)同數(shù)據(jù)巖性分類精度較高,Hyperion次之,WorldView-2數(shù)據(jù)巖性分類精度最低。
[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.
【作者單位】： 中國地質(zhì)大學(xué)信息工程學(xué)院;山東女子學(xué)院;成都理工大學(xué)國土資源部地學(xué)空間信息技術(shù)重點(diǎn)實(shí)驗(yàn)室;中國地質(zhì)大學(xué)公共管理學(xué)院;國家測繪地理信息局四川基礎(chǔ)地理信息中心;
【基金】：國家自然科學(xué)基金項(xiàng)目(41702358,41771444,41201440) 四川省教育廳重點(diǎn)項(xiàng)目(16ZA0090,15ZA0078) 中國地質(zhì)調(diào)查局地調(diào)項(xiàng)目(2017120) 山東高等學(xué)校科技計(jì)劃項(xiàng)目(J15LN11)
【分類號】：P627

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