基于Landsat 8的辽宁弓长岭区遥感蚀变信息提取

doi:10.13278/j.cnki.jjuese.20180093

吉林大学学报(地球科学版) ›› 2019, Vol. 49 ›› Issue (3): 893-901.doi: 10.13278/j.cnki.jjuese.20180093

基于Landsat 8的辽宁弓长岭区遥感蚀变信息提取

贺金鑫, 姜天, 董永胜, 韩凯旭, 马宁, 熊玥

吉林大学地球科学学院, 长春 130061

收稿日期:2018-04-27 出版日期:2019-06-03 发布日期:2019-06-03
作者简介:贺金鑫(1979-),男,教授,博士,主要从事多/高光谱遥感地质,多维地质建模、模拟与可视化方面的研究,E-mail:hejx@jlu.edu.cn
基金资助:
国家自然科学基金项目（41430210）；中国地质调查局项目（DD20160121）

Alteration Information Extraction Based on Remote Sensing of Landsat 8 in Gongchangling Area of Liaoning

He Jinxin, Jiang Tian, Dong Yongsheng, Han Kaixu, Ma Ning, Xiong Yue

College of Earth Sciences, Jilin University, Changchun 130061, China

Received:2018-04-27 Online:2019-06-03 Published:2019-06-03
Supported by:
Supported by National Natural Science Foundation of China(41430210) and Geological Survey Project of the China Geological Survey(DD20160121)

摘要/Abstract

摘要： 在详细解读辽宁弓长岭区Landsat 8影像数据的基础上，结合矿物光谱理论和弓长岭地区（地表植被覆盖严重）的基础地质资料，采用主成分分析法与比值法相结合的方式对该区2017-05和2017-08两个时段的Landsat 8多光谱遥感数据的蚀变异常信息进行了提取。结果表明：利用主成分分析法与比值法相互结合所形成的波段组合比单独运用主成分分析所提取的蚀变异常信息更加明显；此次研究中2017-05数据所提取出的羟基蚀变信息及2017-08数据所提取的铁染蚀变信息主要分布于弓长岭一矿区、二矿区、三矿区和独木-八盘岭矿区地表出露矿体的外围。这也说明将主成分分析法与比值法相结合对于植被覆盖严重区域的蚀变信息提取仍具有较好的效果。

关键词: 多光谱遥感, Landsat 8数据, 主成分分析法, 比值法, 弓长岭铁矿, 弓长岭区

Abstract: Based on a detailed interpretation of Landsat 8 remote sensing data of Gongchangling in Liaoning Province, combined with the theory of mineral spectrum and basic geological data in Gongchangling area (with serious vegetation cover), the alteration anomaly information in 2017-05 and 2017-08 was extracted by using the method of principal component and ratio analysis. The results show that the band combination formed by the method combination of principal component and ratio analyses is more obvious than the abnormal information extracted by principal component analysis alone. The information of hydroxyl alteration extracted from 2017-05 data and the iron dyeing alteration extracted from 2017-08 data are mainly distributed in the periphery of exposed orebodies in Gongchangling No. 1, No. 2, No. 3 and Dumu-Bapanling mining areas. It is also shown that the combination of principal component analysis and ratio method is effective in extracting alteration information in the areas with serious vegetation cover.

Key words: multispectral remote sensing, Landsat 8 data, principal component analysis (PCA), ratio method, Gongchangling iron mine, Gongchangling area

中图分类号:

P627

贺金鑫, 姜天, 董永胜, 韩凯旭, 马宁, 熊玥. 基于Landsat 8的辽宁弓长岭区遥感蚀变信息提取[J]. 吉林大学学报(地球科学版), 2019, 49(3): 893-901.

He Jinxin, Jiang Tian, Dong Yongsheng, Han Kaixu, Ma Ning, Xiong Yue. Alteration Information Extraction Based on Remote Sensing of Landsat 8 in Gongchangling Area of Liaoning[J]. Journal of Jilin University(Earth Science Edition), 2019, 49(3): 893-901.

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基于Landsat 8的辽宁弓长岭区遥感蚀变信息提取

Alteration Information Extraction Based on Remote Sensing of Landsat 8 in Gongchangling Area of Liaoning

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