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REMOTE SENSING FOR LAND & RESOURCES    2014, Vol. 26 Issue (2) : 140-147     DOI: 10.6046/gtzyyg.2014.02.23
Technology Application |
Distribution characteristics of remote sensing information on weak mineralization and alteration in Guizhou
KUANG Zhong1, HUANG Xinxin1, KUANG Shunda2, LU Zhengyan1, LONG Shengqing1
1. Guizhou Academy of Geological Survey, Guiyang 550005, China;
2. Southwest Energy and Mineral Resources Corporation Co, LTD, Guiyang 550004, China
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Abstract  Taking Landsat7 ETM+ as the data source and using "de-interfered anomalous principal component thresholding technique,i.e., DAPCTT",the authors extracted weak mineralization and alteration remote sensing information (i.e. hydroxyl and iron-stain remote sensing anomaly information) in Guizhou Province. As this kind of information contains large quantities of discrete data and uses the grid file form,the authors used the density weighted method to process the surface interpolation of the discrete outliers and drew the contour maps. The contour maps show that the remote sensing anomaly distribution has certain regularity and is in good agreement with the formation, structure and distribution of mineral resources. In combination with geochemical element anomaly distribution map,high resolution remote sensing images and field measured alteration zone data,the comparison and verification were made for the remote sensing anomalies, and the results show that the weak mineralization and alteration remote sensing information extracted by these methods is reliable and can reflect the basic relationships between geological structures,rocks and mining fields. In addition, it can supply new clues to the evaluation of mineral resources potential in Guizhou Province.
Keywords multifocus images      wavelet transform      regional grads     
:  TP753  
Issue Date: 28 March 2014
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MENG Qiangqiang
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MENG Qiangqiang,YANG Guang,TONG Tao, et al. Distribution characteristics of remote sensing information on weak mineralization and alteration in Guizhou[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(2): 140-147.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2014.02.23     OR     https://www.gtzyyg.com/EN/Y2014/V26/I2/140
[1] Regan R D,Taranik J V,Gutman S I.Principles of remote sensing for the exploration geophysicist[M].Society of Exploration Geophysicists,1980.
[2] 地质情报研究所.遥感专辑(第一辑),矿物岩石的可见—中红外光谱及其应用[M].北京:地质出版社,1980. Geological Science and Technology Information Institute. Remote sensing special(the 1st),mineral rock evidently——in infrared spectrum and its application[M].Beijing:Geological Publishing House,1980.
[3] Hunt G R,Salisbury J W.Assessment of landsat filters for rock type discrimination based on intrinsic information in laboratory spectra[J].Geophysics,1978,43(4):738-747.
[4] 张玉君.遥感异常提取方法技术推广教材[M].北京:中国国土资源航空物探遥感中心,2007. Zhang Y J.Remote sensing anomaly draw method technology to popularize teaching material[M].Beijing:China Aero Geophysical Survey and Remote Sensing Center for Land and Resources,2007.
[5] 张玉君,李建民.基岩裸露区蚀变岩遥感信息的提取方法[J].国土资源遥感,1998,10(2):46-53. Zhang Y J,Li J M.The method of abstracting remote sensing information of alterated rocks in the uncovered bedrocks area [J].Remote Sensing for Land and Resources,1998,10(2):46-53.
[6] 刘文兰,张微.遥感构造蚀变异常信息提取及找矿预测——以老挝为例[J].国土资源遥感,2012,24(2):68-74. Liu W L,Zhang W.Remote sensing structural alteration information extraction and ore prognosis:A case study of Laos[J].Remote Sensing for Land and Resources,2012,24(2):68-74.
[7] 杨柏林,杨琨,陈赶良,等.黔桂地区微细浸染型金矿遥感找矿研究[J].贵州地质,1996,13(4):300-310. Yang B L,Yang K,Cheng G L,et al.A study on seeking for carlin-type gold deposits in Guizhou and Guangxi by remote sensing [J].Guizhou geology,1996,13(4):300-310.
[8] 崔敏中.黔西南紫木凼金矿区卫星图像影像特征及成矿机制初探[C]//贵州省遥感学会.贵州遥感论文集.贵阳:贵州省山地资源研究所,1989:68-74. Cui M Z.The satellite image feature and become mineralization pre-test in Zimudang gold deposit in southwest Guizhou[C]//Guizhou Remote Sensing Society.Guizhou Symposium on Remote Sensing.Guiyang:Institute of Mountainous Resource of Guizhou Province,1989:68-74.
[9] 董光贵.贵州贞丰背斜区卫星TM影像特征与金矿关系初探[J].贵州地质,1996,13(4):311-315. Dong G G.A preliminary study on the relationship between salellite TM image features of Zhenfeng anticline and gold deposits of southweatern Guizhou[J].Guizhou geology,1996,13(4):311-315.
[10] 况忠,龙胜清,曾禹人,等.黔西南地区遥感构造与金矿的关系及找矿预测[J].国土资源遥感,2012,24(1):160-165. Kuang Z,Long S Q,Zeng Y R,et al.The relationship between remote sensing structures and gold deposits and ore-prospecting prognosis in southwest Guizhou[J].Remote Sensing for Land and Resources,2012,24(1):160-165
[11] 况顺达,姚智,刘沛,等.黔东南铜金矿遥感预测及方法技术研究[M].贵阳:贵州省地质调查院,2002. Kuang S D,Yao Z,Liu P,et al.The copper gold mine forecast and method technology of remote sensing are studied in southeast Guizhou[M].Guiyang;Guizhou Geological Survey,2002.
[12] 范素英,郑旭,徐雯佳,等.矿化蚀变信息提取及数据处理方法研究[C]//单杰.第十八届中国遥感大会论文集.北京:科学出版社,2012:1078-1084. Fan S Y,Zheng X,Xu W J,et al.Information of remote sensing mineralization to draw and the data research of processing technique[C]//Shan J.Proceeding of the 18th China Symposium on Remote Sensing.Beijing:Science Press,2012:1078-1084.
[13] 贵州省地质矿产局.贵州省区域地质志[M].北京:地质出版社,1987. Bureau of Geology and Mineral Exploration and Development of Guizhou Province.Regional geology of Guizhou Province[M].Beijing:Geological Publishing House,1987.
[14] 贵州省地质矿产局.贵州省区域矿产志[M].贵阳:贵州省地质矿产局,1986. Bureau of Geology and Mineral Exploration and Development of Guizhou Province. Regional mineral geology of Guizhou Province[M].Guiyang:Bureau of Geology and Mineral Exploration and Development of Guizhou Province,1986.
[15] 汤国安,杨昕.ArcGIS地理信息系统空间分析实验教程[M].北京:科学出版社,2006. Tang G A,Yang X.ArcGIS spatial analysis geography information systematic experiment course[M].Beijing:Science Press,2006.
[16] 朱亮璞.遥感地质学[M].北京:地质出版社,2011:148-149. Zhu L P.Remote sensing geology[M].Beijing:Geological Publishing House,2011:148-149.
[17] 况忠,韩宝智,朱顺才,等.利用ETM+遥感影像图对贵州断裂构造的再认识[C]//单杰.第十八届中国遥感大会论文集.北京:科学出版社,2012:872-882. Kuang Z,Han B Z,Zhu S C,et al.Use ETM+ remote sensing image recongnition of fault structure in Guizhou[C]//Shan J.Proceeding of the 18th China Symposium on Remote Sensing.Beijing:Science Press,2012:872-882.
[18] 刘建中.贵州水银洞金矿床矿石特征及金的赋存状态[J].贵州地质,2003,74(1):30-34. Liu J Z.Ore characteristics and gold occurrence of the Shuiyindong gold deposit in Guizhou[J].Guizhou Geology,2003,74(1):30-34.
[19] 黄建国,郝家栩,张敏,等.二叠系龙潭煤系与黔西南金矿的关系研究[J].黄金,2008,29(8):10-14. Huang J G,Hao J X,Zhang M,et al.Study on relationship between Permian Longtan coal system and Southwest Guizhou gold deposit[J].Gold,2008,29(8):10-14.
[20] 冯琳,张竹如.泥堡金矿与水银洞金矿地质特征初步对比[J].贵州地质,2005,22(1):22-25. Feng L,Zhang Z R.Initiative contrast of geological characters at the Nipu and Shuiyindong gold deposits[J].Guizhou Geology,2005,22(1):22-25.
[21] 王研耕.贵州西南部红土型金矿成矿背景及其控制因素[J].贵州地质,1998,15(4):299-304. Wang Y G.Geological setting and controls for latentic gold mineralization in Southwest Guizhou[J].Guizhou geology,1998,15(4):299-304.
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