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Identification of spectrally similar materials using the USGS Tetracorder algorithm: the calcite-epidote-chlorite problem

机译:使用USGS Tetracorder算法识别光谱相似的材料:方解石-埃培特-亚氯酸盐问题

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A scheme to discriminate and identify materials having overlapping spectral absorption features has been developed and tested based on the U.S. Geological Survey (USGS) Tetracorder system. The scheme has been applied to remotely sensed imaging spectroscopy data acquired by the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument. This approach was used to identify the minerals calcite, epidote, and chlorite in the upper Animas River watershed, Colorado. The study was motivated by the need to characterize the distribution of calcite in the watershed and assess its acid-neutralizing potential with regard to acidic mine drainage. Identification of these three minerals is difficult because their diagnostic spectral features are all centered at 2.3 μm, and have similar shapes and widths. Previous studies overestimated calcite abundance as a result of these spectral overlaps. The use of a reference library containing synthetic mixtures of the three minerals in varying proportions was found to simplify the task of identifying these minerals when used in conjunction with a rule-based expert system. Some inaccuracies in the mineral distribution maps remain, however, due to the influence of a fourth spectral component, sericite, which exhibits spectral absorption features at 2.2 and 2.4 μm that overlap the 2.3-μm absorption features of the other three minerals. Whereas the endmember minerals calcite, epidote, chlorite, and sericite can be identified by the method presented here, discrepancies occur in areas where all four occur together as intimate mixtures. It is expected that future work will be able to reduce these discrepancies by including reference mixtures containing sericite.
机译:基于美国地质调查局(USGS)Tetracorder系统,已经开发并测试了一种鉴别和识别具有重叠光谱吸收特征的材料的方案。该方案已应用于由机载可见和红外成像光谱仪(AVIRIS)仪器获取的遥感成像光谱数据。该方法用于识别科罗拉多州阿尼马斯河上游流域的方解石,埃迪奥地石和绿泥石矿物。这项研究的动机是需要表征方解石在流域中的分布并评估其在酸性矿山排水方面的酸中和潜力。很难识别这三种矿物,因为它们的诊断光谱特征都集中在2.3μm处,并且具有相似的形状和宽度。由于这些光谱重叠,以前的研究高估了方解石的丰度。已发现使用包含不同比例的三种矿物的合成混合物的参考库可简化与基于规则的专家系统结合使用时识别这些矿物的任务。然而,由于第四种光谱成分绢云母的影响,矿物分布图中仍存在一些误差,其在2.2和2.4μm处表现出光谱吸收特征,与其他三种矿物的2.3μm吸收特征重叠。尽管可以通过此处介绍的方法来识别方解石,方解石,绿泥石和绢云母的最终矿物,但在所有这四种矿物以紧密混合物的形式一起出现的区域却出现了差异。预计未来的工作将能够通过包含含绢云母的参考混合物来减少这些差异。

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