| 冯园园,赵宝聚,李大兜,耿安凯,王泽,李晓楠,刘力.基于混合像元分解的植被抑制及遥感蚀变信息提取——以柬埔寨松莫县乌可列扩金矿床为例[J].矿产勘查,2025,16(4):822-833 |
| 基于混合像元分解的植被抑制及遥感蚀变信息提取——以柬埔寨松莫县乌可列扩金矿床为例 |
| Vegetation suppression and remote sensing alteration information extraction based on mixed pixel decomposition: A case of the Wukeliekuo gold deposit in Songmo County, Cambodia |
| 投稿时间：2023-07-19 |
| DOI：10.20008/j.kckc.202504013 |
| 中文关键词: 植被抑制 混合像元 蚀变信息 主成分分析法 乌可列扩金矿区 |
| 英文关键词: vegetation suppression mixed pixel alteration information principal component analysis Ukele gold mining area |
| 基金项目:本文受中国地质调查局项目(DD20208006)资助。 |
|
| 摘要点击次数: 2149 |
| 全文下载次数: 1247 |
| 中文摘要: |
| 遥感影像技术在地质学特别是矿产勘查领域得到了广泛应用。但在高植被覆盖区，影像的混合光谱难以有效分解，且提取的岩石信息为弱信息，岩性分类、矿物识别较为困难，难于客观有效提取与成矿有关的遥感蚀变信息。本文应用混合像元分解的方法技术区分出混合像元中各类干扰信息的反射率值及其所占丰度值，从混合像元光谱中减去各干扰因素的反射率值及其所占份额，运用遥感影像植被抑制方法对光学遥感影像数据进行预处理，完成土壤或岩石光谱的重建。采用 Landsat7、Landsat8、Aster和 World-view-2共 4种不同类型的多源遥感数据组合，对于消除干扰因素影响后的新图像，用传统的主成分分析方法进行蚀变信息提取，大幅提高遥感蚀变信息提取的可靠性。提取的蚀变信息在已知旧露采面、矿石堆及尾矿渣堆处均有高值异常显示，与实际情况吻合较好。 |
| 英文摘要: |
| Remote sensing image technology has been widely used in geology, especially in mineral explora-tion. It is difficult to decompose the mixed spectra of the images in the high vegetation coverage area, and the ex-tracted rock information is weak information, so it is difficult to classify the lithology and identify the minerals, ex-tract the alteration information related to mineralization objectively and effectively. Using the method of mixed pixeldecomposition, the reflectivity value and the abundance value of various interference information in the mixed pixelare distinguished, and the reflectivity value and the share of each interference factor are subtracted from the spec-trum of the mixed pixel, the vegetation suppression method is used to preprocess the optical remote sensing imagedata and reconstruct the spectrum of soil or rock. In this paper, four different types of multi-source remote sensingdata, including Landsat 7, Landsat 8, Aster and Worldview-2, are combined to extract alteration information fromnew images after removing interference factors by traditional principal component analysis (PCA), the reliability ofremote sensing alteration information extraction is greatly improved. The extracted alteration information shows highvalue anomaly in known old surface, ore pile and tailings pile, which is in good agreement with the actual situation. |
|
查看全文
查看/发表评论 下载PDF阅读器 |
| 关闭 |
|
|
|