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EnMAP星载高光谱数据蚀变矿物填图OA

Application of EnMAP spaceborne hyperspectral data to alteration mineral mapping

中文摘要英文摘要

EnMAP星载高光谱数据在信噪比、光谱响应稳定性方面具有较为突出的优势,为评估EnMAP星载高光谱数据在区域尺度矿物填图中的适用性与可靠性,基于2025年获取的EnMAP L2A级地表反射率数据,对新疆雪米斯坦西部地区开展蚀变矿物识别与空间分布研究.针对星载高光谱数据空间分辨率低、混合像元分解困难等特点,通过依次开展MNF降维、PPI端元提取与n维可视化分析,提取白云母、绿泥石、白云石和方解石等典型蚀变矿物端元,并结合光谱角匹配(SAM)与混合调谐匹配滤波(MTMF)实现矿物识别.结果表明,EnMAP数据能够有效识别研究区主要蚀变矿物,其矿物类型及空间分布格局与机载CASI/SASI高光谱数据结果具有较好一致性,其在区域尺度矿物填图与成矿预测研究中具有良好的应用潜力.

The EnMAP spaceborne hyperspectral sensor has notable advantages in signal-to-noise ratio and spectral response stability.To evaluate the applicability and reliability of EnMAP hyperspectral data for regional-scale mineral mapping,this study investigated alteration mineral identification and spatial distribution in the western Xuemistan area,Xinjiang,using EnMAP Level-2A surface reflectance data acquired in 2025.Considering the low spatial resolution of spaceborne hyperspectral data and the associated mixed-pixel effects,a workflow integrating Minimum Noise Fraction(MNF)transformation,Pixel Purity Index(PPI)endmember extraction,and n-dimensional visualization analysis was applied to extract representative alteration mineral endmembers,including muscovite,chlorite,dolomite,and calcite.Mineral identification was then performed using the Spectral Angle Mapper(SAM)and Mixture-Tuned Matched Filtering(MTMF)methods.The results show that EnMAP data effectively identify the major alteration minerals in the study area.The derived mineral types and spatial distribution patterns are consistent with those obtained from airborne CASI/SASI hyperspectral data,indicating that EnMAP hyperspectral data have strong potential for regional-scale mineral mapping and mineral prospectivity analysis.

赵洪萱;刘洪成;谭宏婕;田建吉;张川

铀资源探采与核遥感全国重点实验室,北京 100029||核工业北京地质研究院,北京 100029铀资源探采与核遥感全国重点实验室,北京 100029||核工业北京地质研究院,北京 100029||北京大学地球与空间科学学院,北京 100871中国地质大学(北京)地球科学与资源学院,北京 100083铀资源探采与核遥感全国重点实验室,北京 100029||核工业北京地质研究院,北京 100029铀资源探采与核遥感全国重点实验室,北京 100029||核工业北京地质研究院,北京 100029

天文与地球科学

EnMAP高光谱矿物填图混合调谐匹配滤波(MTMF)

EnMAPhyperspectral remote sensingmineral mappingMTMF

《世界核地质科学》 2026 (1)

188-197,10

10.3969/j.issn.1672-0636.2026.01.016

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