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首页> 外文期刊>International journal of remote sensing >Integrating visible, near-infrared and short-wave infrared hyperspectral and multispectral thermal imagery for geological mapping at Cuprite, Nevada: a rule-based system
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Integrating visible, near-infrared and short-wave infrared hyperspectral and multispectral thermal imagery for geological mapping at Cuprite, Nevada: a rule-based system

机译：整合可见，近红外和短波红外高光谱和多光谱热成像仪，用于在内华达州库珀特的地质制图：基于规则的系统

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摘要

Previous research has shown that integrating hyperspectral visible and near-infrared (VNIR) / short-wave infrared (SWIR) with multispectral thermal infrared (TIR) data can lead to improved mineral and rock identification. However, inconsistent results were found regarding the relative accuracies of different classification methods for dealing with the integrated data set. In this study, a rule-based system was developed for integration of VNIR/SWIR hyperspectral data with TIR multispectral data and evaluated using a case study of Cuprite, Nevada. Previous geological mapping, supplemented by field work and sample spectral measurements, was used to develop a generalized knowledge base for analysis of both spectral reflectance and spectral emissivity. The characteristic absorption features, albedo and the location of the spectral emissivity minimum were used to construct the decision rules. A continuum removal algorithm was used to identify absorption features from VNIR/SWIR hyperspectral data only; spectral angle mapper (SAM) and spectral feature fitting (SFF) algorithms were used to estimate the most likely rock type. The rule-based system was found to achieve a notably higher performance than the SAM, SFF, minimum distance and maximum likelihood classification methods on their own.
机译：先前的研究表明，将高光谱可见光和近红外（VNIR）/短波红外（SWIR）与多光谱热红外（TIR）数据相集成可以改善矿物和岩石的识别。但是，关于处理集成数据集的不同分类方法的相对准确性，发现不一致的结果。在这项研究中，开发了基于规则的系统，用于将VNIR / SWIR高光谱数据与TIR多光谱数据集成在一起，并使用内华达州Cuprite的案例进行了评估。以前的地质制图，再加上野外工作和样品光谱测量，被用来建立一个用于分析光谱反射率和光谱发射率的通用知识库。使用特征吸收特征，反照率和光谱发射率最小值的位置来构造决策规则。仅使用连续介质去除算法从VNIR / SWIR高光谱数据中识别吸收特征。谱角映射器（SAM）和谱特征拟合（SFF）算法用于估计最可能的岩石类型。发现基于规则的系统本身比SAM，SFF，最小距离和最大似然分类方法具有明显更高的性能。

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  • 来源
    《International journal of remote sensing》 |2010年第8期|P.1733-1752|共20页
  • 作者

    XIANFENG CHEN; TIMOTHY A. WARNER; DAVID J. CAMPAGNA;

  • 作者单位

    Slippery Rock University, Slippery Rock, PA 16057, USA;

    West Virginia University, Morgantown, WV 26506, USA;

    rnWest Virginia University, Morgantown, WV 26506, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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