基于多元参照光谱的SAM岩性划分方法
作者简介:帅爽(1988-),男,硕士,工程师,研究方向为遥感地质。E-mail: 100821844@qq.com
收稿日期: 2015-03-16
要求修回日期: 2015-04-30
网络出版日期: 2016-01-10
基金资助
中国地质调查局“航空地球物理和遥感探测技术研发与应用示范”项目(12120113099900)
Lithological Mapping by Multiple Reference Spectra Based SAM
Received date: 2015-03-16
Request revised date: 2015-04-30
Online published: 2016-01-10
Copyright
光谱角制图(SAM)是一种光谱匹配方法,通过量化目标地物光谱与已知参照光谱的相似程度来判断目标地物的类型,广泛应用于多光谱遥感岩性识别。目前,岩石单元训练区内像元的均值光谱,往往作为代表该岩石单元的参照光谱来进行光谱角制图,而使用均值光谱作为参照光谱库的方法,并未考虑岩石单元内部固有的光谱差异性,很大程度上影响了SAM分类效果。为了消除SAM岩性划分时岩石单元内部的光谱差异的影响,本文采用了一种多元参照光谱的SAM岩性划分方法。首先,依据研究区已有地质资料和Landsat-8影像特征,选定各类岩石单元训练区;接着进行各岩石单元训练区内部像元的光谱差异性分析,和各训练区之间的样本可分离性分析,分别使用均值参照光谱库的SAM方法和多元参照光谱库的SAM方法对研究区Landsat-8影像进行了岩性划分实验。研究结果表明,多元参照光谱库的SAM岩性分类方法很好地改善了岩石单元内部光谱差异性对均值参照光谱库的SAM岩性分类方法的影响,分类精度显著提高。
帅爽 , 张志 , 王少军 , 陈安 . 基于多元参照光谱的SAM岩性划分方法[J]. 地球信息科学学报, 2016 , 18(1) : 133 -140 . DOI: 10.3724/SP.J.1047.2016.00133
The spectral angle mapper (SAM) is a spectral matching method. This method can determine the types of target objects through quantifying the spectral similarity between a target pixel spectrum and a known reference spectrum.SAM has been widely used in rock type identification that uses multispectral data. In the most existing studies, a mean reflectance spectrum of a specific lithological training area has been used as the reference spectrum for the lithological class in SAM. However, the SAM, which uses the mean spectrum, does not take into account the spectral variability, which is an inherent property of many rocks. Andthe spectral variabilityseriously affects SAM classification results.In order to eliminate the impactof the spectral variability inside the lithological classes, a SAM method based on multiple reference spectra is used in this research. First, a geological map of the study area was used to select training areas forfive lithological classes from the Landsat-8 data of the study area.Then the spectral variability inside the lithological classes and the separability between the lithological classeswereexamined. At last, both ofthe SAM with mean reference spectrum and the multiple reference spectra based SAM wereused in lithological mapping of Landsat-8 data in the study area.The results show that the multiple reference spectra based SAM successfully eliminated the influence of the spectral variability on the SAM with mean reference spectrum, and madesignificant improvement tothe accuracy of lithological mapping.
Fig. 1 The choice of lithological training areas图1 岩石单元训练区的选择 |
Fig. 2 The mean spectral curves and pixels’ spectral curves of different lithological training areas图2 各岩石单元训练区像元光谱曲线和均值光谱曲线 |
Tab. 1 The mean angle and standard deviation between pixels of different lithological training areas表1 各岩石单元训练区内像元间光谱角均值、标准差表 |
K1 | K2 | K3 | E1 | E2 | |
---|---|---|---|---|---|
均值 | 2.5742 | 3.2127 | 2.7956 | 3.4711 | 2.7143 |
标准差 | 1.4546 | 1.6973 | 1.2803 | 1.8437 | 1.4631 |
Tab. 2 The J-M values of different lithological training areas表2 各岩石单元间J-M距离 |
J-M距离 | K1 | K2 | K3 | E1 | E2 |
---|---|---|---|---|---|
K1 | 1.989 | 1.998 | 1.993 | 2.000 | |
K2 | 1.989 | 1.869 | 1.960 | 1.995 | |
K3 | 1.998 | 1.869 | 1.989 | 1.981 | |
E1 | 1.993 | 1.960 | 1.989 | 2.000 | |
E2 | 2.000 | 1.995 | 1.981 | 2.000 |
Tab. 3 The optimization of different lithological training areas表3 各岩石单元训练区像元优化情况 |
训练区 | K1 | K2 | K3 | E1 | E2 |
---|---|---|---|---|---|
原始像元数 | 64 | 30 | 64 | 36 | 63 |
剩余像元数 | 60 | 28 | 55 | 27 | 55 |
像元剔除率(%) | 6.25 | 6.67 | 14.06 | 25.00 | 12.70 |
Tab. 4 Confusion matrices of the classification results of two SAM methods表4 2种SAM岩性划分结果精度评价 |
类别 | 均值参照光谱库的SAM | 多元参照光谱库的SAM | |||
---|---|---|---|---|---|
生产者精度(%) | 用户精度(%) | 生产者精度(%) | 用户精度(%) | ||
K1 | 68.21 | 95.98 | 93.39 | 96.93 | |
K2 | 58.80 | 92.98 | 80.03 | 63.44 | |
K3 | 89.07 | 64.48 | 89.43 | 80.44 | |
E1 | 45.21 | 34.78 | 72.10 | 93.66 | |
E2 | 91.40 | 90.96 | 85.11 | 98.06 | |
总体精度 | 76.8057 | 86.4557 | |||
Kappa系数 | 0.6989 | 0.8250 |
Fig. 3 The classifications effects of two SAM methods图3 2种SAM方法的分类效果图 |
The authors have declared that no competing interests exist.
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