基于二次散射非线性混合模型的遥感地质填图
首发时间:2013-04-12
摘要:高光谱遥感利用光谱特征可以识别出大部分的岩石和矿物,遥感地质填图可以补充野外填图的成果。传统的遥感地质填图方法多针对部分区域,且不考虑一个像元中多种地物共生组合,难以反映复杂的地质分布特征。因此,本文提出了k(k≥2)类地物的填图规则:针对线性混合模型解混精度不高的问题,使用二次散射模型对美国内华达州Cuprite地区AVIRIS数据进行光谱解混,根据解混结果及所提出的填图规则进行地质填图,对比Clark等的实际填图结果,基于二次散射模型较线性模型的填图更加接近真实矿物分布,且使用k(k≥2)类地物的填图规则的填图结果比只填一类地物的填图结果细节丰富,更加接近Clark等人的填图结果。
关键词: 高光谱图像 光谱解混 线性混合模型 非线性模型 二次散射模型 遥感地质填图
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Remote Sensing Geology Mapping Based on Secondary Scattering Mixture Model
Abstract:Hyperspectral remote sensing can help identify most of the rocks and minerals by using spectral characteristics, and remote sensing geological mapping can complement the results of the field mapping. Traditional geological mapping methods conduct mapping to partial areas and has ignored the situation that a variety of feature has symbiotic combination in one pixel. Therefore, this paper proposed k (k ≥ 2) class mapping rules based on the unmixing result. The Nevada Cuprite AVIRIS data is used in the experiment and mapping results based on the secondary scattering model and the linear model are given. Actual mapping results of Clark's et. al are taken as reference and comparison results have shown that mapping results based on the secondary scattering mixture model are closer to actual ground feature distribution than those based on the linear model, and compared to the results with one class mapping rule, the results using k (k ≥ 2) class mapping rules have richer details and are closer to Clark's et. Al results.
Keywords: hyperspectral imagery spectral unmixing linear spectral model nonlinear model secondary scattering model geological mapping
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