首页> 外文会议>IEEE International Geoscience and Remote Sensing Symposium >Study on the extraction of iron mineralized alteration information in vegetation covered areas based on remote sensing ASTER data: A case study of Fenghuangshan iron deposit located in Lanling County, Shandong Province, China
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Study on the extraction of iron mineralized alteration information in vegetation covered areas based on remote sensing ASTER data: A case study of Fenghuangshan iron deposit located in Lanling County, Shandong Province, China

机译:基于遥感ASTER数据的植被覆盖区铁矿化蚀变信息提取研究-以山东省兰陵县凤凰山铁矿床为例

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Remotely sensed mineralized alteration information is of great significance to geological prospecting and extracting such alteration information in high vegetated areas is difficult. Based on ASTER data, the following processes are performed. First, the ASTER data are geometrically corrected and atmospherically corrected, and water and shadow are masked. Then, principal component analysis method is applied to extract ferric contamination information, which is enhanced and classified by thresholding. Finally, mineralization anomaly regions are delineated with reference to known ore deposits and related alterations. In the fieldwork, the extracted alteration information was verified, proving that the ASTER data are of capacity to acquire minerals' spectral characteristics in the short wave infrared range, which effectively facilitate geological prospecting in densely vegetated regions.
机译:遥感矿化蚀变信息对地质找矿具有重要意义,在高植被区提取此类蚀变信息十分困难。基于ASTER数据,执行以下处理。首先,对ASTER数据进行几何校正和大气校正,并遮盖水和阴影。然后,应用主成分分析方法提取铁污染信息,并通过阈值对其进行增强和分类。最后,参照已知的矿床和相关的变化划定了矿化异常区域。在野外工作中,对提取的蚀变信息进行了验证,证明了ASTER数据具有在短波红外范围内获取矿物光谱特征的能力,从而有效地促进了植被茂密地区的地质勘探。

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