云南维西—兰坪铅锌多金属成矿带遥感信息融合与成矿预测
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
随着从地表找矿到深部找矿的趋向,地质找矿从传统找矿方法发展到多元信息融合找矿理论的实践应用。多元是指把地质、物探、化探、遥感等信息叠加分析,并把定性与定量预测相结合,从而形成一套丰富的成矿理论,为已有矿区的深部、外围及隐伏矿体的找矿提供科学依据。
     本文是基于国家矿产远景调查项目《云南维西—兰坪(通甸-白汉场)地区1/5万矿产远景调查》为依托,以地理信息系统为平台,对多元地学空间信息(地、物、化、遥等)进行叠加分析,运用综合成矿信息预测的理论,在研究区已有矿点的基础上,寻找新资源,增加资源储量。维西-兰坪研究区位于三江并流区域,成矿条件良好,在研究区周边已发现众多矿床。本文在已有资料的基础上,以综合成矿信息预测理论为指导,融合地、物、化、遥多源找矿信息,确定综合信息找矿模式,以下为获得的认识及成果:
     1、多源地学空间信息数据库的建立,将地、物、化、遥相结合,对控矿因素及找矿标志的划分起到重要作用,从而可以有效地确定找矿信息;
     2、分析地物的光谱特征,研究岩浆岩、变质岩的光谱曲线特性,运用遥感异常蚀变信息的提取方法,对研究区进行铁化、泥化蚀变矿物的提取;
     3、对研究区的遥感影像ETM+、SPOT5数据,采用Erdas数字图像处理软件对其进行信息解译及线环构造的提取,并运用金属矿产资源分析系统Morpas对提取的线性构造进行等密度、条数、中心对称度、优益度等定量分析,圈定遥感异常信息。研究区内的北东与北西向相交处利于矿体的富集;
     4、对飘雪岩、桃花村典型区域划分网格单元,计算单变量、复合变量的信息值,确立综合找矿的信息模式,优选出7个找矿靶区,其中Ⅰ类靶区1个,Ⅱ类靶区2个,Ⅲ类靶区4个。
Geological prospecting has developed from the traditional prospecting methods to the practical application of the theory of multi-source information fusion prospecting as the trend of ore prospecting from the surface to the deep. Multi-source refers to the superposition analysis of information such as geology, geophysical exploration, geochemical exploration and remote sensing, etc, and to combine the qualitative prediction and quantitative prediction, thus to form a rich metallogeny theory, and to provide a scientific basis for the prospecting of the deep, peripheral and concealed ore--bodies of the existing mine.
     Based on the national research project of the mineral vision "the research project of the 1 to 50000 mineral vision of Weixi-Lanping "Tongdian-Baihanchang" area in Yunnan province", and platformed with a geographical information system, this article superimposed and analyzed the multi-source geo-spatial information such as geology, geophysical exploration, geochemical exploration and remote sensing, etc., and used an theory of integrated metallogenic information prediction to find new resources to increase the reserves on the basis of the mining point in the study area. The study area Weixi—Lanping is located in the Three Parallel Rivers region, the mineralization is in good condition, and there has found a number of deposits around the study area. In this paper, based on the existing data, and under the guide of the theory of an integrated metallogenic information prediction, we fuse the multi-source prospecting information such as geology, geophysical exploration, geochemical exploration and remote sensing, etc. to determine the comprehensive information prospecting model. The knowledge and the results obtained are as follows:
     1. The establishment of the multi-source geo-spatial information database combined geology, geophysical exploration, geochemical exploration and remote sensing and played an important role in the division of the ore-controlling factors and prospecting marks. It will effectively determine the prospecting information.
     2. We can extract Iron-based and Clay-alteration minerals of the study area by analyzing the spectral characteristics of surface features, studying the spectral curve characteristics of the magmatite and metamorphic rocks and using the extraction method of the information of remote sensing abnormal alteration.
     3. Interprate information and extract line and ring structure to the remote sensing images ETM, SPOT5 data in the study area using Erdas digital image processing software, and analyze quantitatively to the lineament extraction extracted such as equidensity, number of branches, center symmetry and excellent benefits degrees, ect. using Metallic Mineral Resources Analysis System Morpas to delineate remote sensing Exception Information. The north-east and north-west to the intersection of the study area conducives to the enrichment of ore body.
     4. Divide into a grid cell to the typical region of snowing right rock and Taohua village, calculate information value of the one-variable and complex variable, establish an integrated information model of prospecting and optimize seven oreprospecting target area, including 1 classⅠ,2 classⅡand 4 classⅢtarget area.
引文
[1]MacDonald, I. R., Reilly, J. F., Jr, Best, S. E., venkataramaiah, R., Sassen, R., Amos, J., and
    Guinasso, N. L. Jr.,1996. A remote-sensing inventory of active oil seeps and chemosynthetic communities in the northern Gulf of Mexico,in Schumacher, D., and Abrams, M. A., eds., Hydrocarborn migration and its near-surface expression:American Association of Petroleum Geologists Memoir66[J], pp27-37
    [2]Roger N.Clark, Gregg A. Swayze, and Andrea Gallagher.1993.Mapping with Imaging Spectroscopy[C]. U. S. geological Survey, office of Mineral Resources Bulletin 2009:141-150
    [3]孙家柄,舒宁,关泽群.遥感原理、方法和应用[M],北京:测绘出版社,1997.
    [4]王洪华,等.基于多进制小波变换的遥感影像融合[J].测绘学院学报,2001(9).
    [5]CPOHLJL. Vangenderenmultisensorimagefusioninremotesensing:Concepts, methodsandappli cations[J].1998,19(5):823-854.
    [6]王智均,李德仁,李清泉.利用小波变换对影像进行融合的研究[J].武汉测绘科技大学学报,2000,25(2):137-141.
    [7]OrfinnTaxt, AnneHSchistadSolberg. Informationfusioninremotesensing[J]. VistasinAstro nomy,1997,41 (3):337-342.
    [8]翁永玲,田庆久.遥感数据融合方法分析与评价综述[J].遥感信息,2003.3
    [9]贾永红.多源遥感数据融合[J].遥感技术应用,2000,15(1):41-44
    [10]赵书河.多源遥感影像融合技术与应用[M].南京大学。2008
    [11]Campbell N A.1993. Towards more quantitative extraction of information from remotely sensed data[M]. Proceedings Advanced Remoe Sensing Conference. Sydney. Australia.2:29-40.
    [12]Carper WJ. Lillesand TM and Kiefer RW.1990. The use of intensity Hue Sturation transformations for merging SPOT panchromatic and multi-spectral images[J]. Phtgrammetric Engineering & Remote Sensing.56(4)459-467.
    [13]Chavez PS. Sides S C and Anderson JA.1991.Comparison of three different methods to merge multiresolution and multispectral data:Landsat TM and SPOT panchromatic[J]. Photogrammetric Engineering & Remote Sensing.57:295-303.
    [14]Chibani Y and Houacine A.2002. The joint use of HIS transform and redundant wavelet decomposition for fusing multi spectral and panchromatic images [J]. International Journal of Remoe Sensing.23(18):3821-3833.
    [15]Ehlers M.1991. Multisensor image fusion techniques in remote sensing[J]. ISPRS Journal of Photogrammetry and Remote Sensing.46:19-30.
    [16]Garguet-Duport B. Girel J. Chassery J and Pautou G.1996. The use of multiresolution analysis and wavelets transform for merging SPOT panchromatic and multispectral image data[J]. Photogrammetric Engineering & Remote Sensing.62:1057-1066
    [17]Griffiths GH.1988. Monitoring urban change from Landsat TM and SPOT satellite imagery by image differencing[C]. Proceedings of IGARSS'88 sumposium. Edinburgh. Scotland.13-16. Sept.IEEE88CH2497-6. pp 493-497.
    [18]Kiema J B K.2002. Texture analysis and data fusion in the extraction of topographic objects from satellite umagery[J]. International Journal of Remote Sensing.23(4)767-776.
    [19]Liu J G.2000. Smoothing Filter-based Intensity Modulation:a spectral preserve image fusion technique for improving spatial details[J]. International Journal of Remote Sensing.21(18):3461-3472.
    [20]Munechika C K. Wrnich J S. Slvaggio C and Schott J R.1993. Resolution enhancement of multispectral image data to improve clasifiction accuracy[J]. Photogrammetric Engineering & Remote Sensing.59:67-72.
    [21]Pellemans A H J M. Jordans R W L and Allewijn R.1993. Merging multispectral and panchromatic SPOT images with respect to the radiometric properties of the sensor[J]. Photogrammetric Engineering & Remote Sensing.59(1):81-87
    [22]Petraakos M. Benediktsson J A. and Kanellopoulos I.2001.The effect of classifier agreement on the accuracy of the combined classifier in decision evel fusion [J]. IEEE Transactions on Geoscience & Remote Sensing.39(11):2539-2546.
    [23]Pohl C and Genderen J L Van..1998 Multisensor image fusion in remote sensing:concepts. Methods and applications [J]. International Journal of Remote Sensing.19 (5):823-854.
    [24]Ranchin T and Wald L.1993. The wavelet transform for the analysis of remotely sensed images [J]. International Journal of Remote Sensing.14 (3):615-619.
    [25]Ranchin T and Wald L.2000. Fuision of high spatial and spectral resolution images: the ARSIS concept and its implementation [J].Photogrammetric Engineering & Remote Sensing.66 (1):49-61.
    [26]Saraf A K.1999. IRS-1C-LISS-III and Pan data fusion:an approach to improve remote sensing based mapping techniques [J]. International Journal of Remote Sensing.20 (10): 1929-1934.
    [27]Schetselaar E M.1998. Fusion by the HIS transform:should we use cylindrical or spherical coordinates [J]. International Journal of Remote Sensing.19 (4):759-765.
    [28]Senthil A K and Majumder K L.2001. Majumder Information fusion in tree classifiers [J].International Journal of Remote Sensing.22 (5):861-869.
    [29]Shaban M A and Dikshit 0.2002. Evaluation of the merging of SPOT multispectral and panchromatic data for classification of an urban environment [J]. International Journal of Remote Sensing23 (2):249-262.
    [30]Sheffigara V K.1992. A generalized component substitution technique for spatial enhancement of the use of multi-spectral images using a higher-resolution data set [J]. Photogrammetric Engineering & Remote Sensing.58 (5):561-567.
    [31]Sunar F and Musaoglu N.1998. Merging multiresolution SPOT P and Landsat TM data: the effects and advantages [J]. International Journal of Remote Sensing.19 (2):219-224.
    [32]Tapiador F J and Casanova J L.2002. An algorithm for the fusion of images based on Jaynes'maximum entropy method [J]. International Journal of Remote Sensing.23 (4): 777-785.
    [33]Van der meer F.1997. What does multisensor image fusion add in terms of information content for visual interpretation [J]. International Journal of Remote Sensing.18 (2):445-452.
    [34]Welch R and Manfred Ehlers.1987. Merging multiresolution SPOT HRV and Lndsat TM data[J]. Photogrammetric Engineering & Remote Sensing.53(3):301-303.
    [35]Yocky D A.1996. Multiresolution wavelet decomposition image of Landsat TM and SPOT P data [J]. Photogrammetric Engineering & Remote Sensing.62:1067-1074.
    [36]Zhang Y.1999. A new merging mothod and its spectral and spatial effects [J]. International Journal of Remote Sensing.20 (10):2003-2014.
    [37]Zhou J. Civco D L and Silander J A.1998. A wavelet transform method to merge Landsat TM and SPOT panchromatic data [J]. International Journal of Remote Sensing.19 (4): 743-757.
    [38]方勇.证据推理应用于多源信息融合分析[J].遥感学报.2000.4(2):106-111.
    [38]贾永红.李德仁.孙家抦.刘继林.四种HIS变换用于SAR与TM影像复合的比较[J].1998.2(2):103-106.
    [39]李军.多源遥感影像融合的理论、算法和实践[D].武汉测绘科技大学博士学位论文.1999.
    [40]孙家抦,刘继琳,李军.多源遥感影像融合[J].遥感学报.1998.2(1):47-50 [41]Liu C P et al.2001. " Multi-source Remote Sensing Data Fusion Using Fuzzy Self-organization Mapping Network and Modified Dempster-Shafer Evidential Reasoning Method to Classification" [C].the second international conference of multi-spectral image processing & pattern recognition of SPIE. East-China Technology University.4556:71-79.
    [42]张永生,巩丹超等。要分辨率遥感卫星应用---成像模型、处理算法及应用技术[M]。科学出版社。2004
    [43]张永生,戴晨光,张云彬等。天基多源遥感信息融合——理论、算法与应用系统[M]。科学出版社。2005.
    [44]朱亮璞,遥感地质学[M]。北京:地质出版社,1994
    [45]梅安新,彭望碌,秦其明等,遥感导论[M]。北京:高等教育出版社,2001
    [46]章孝灿,黄智才,赵元洪.遥感数字图像处理[M].杭州:浙江大学出版社,1997,187-90
    [47]党安荣,王晓栋ERDASIMAGINE遥感图像处理方法[M].北京:清华大学出版社,2003.
    [48]赵英时等.遥感应用分析原理与方法[M]。科学出版社2004
    [49]KVani, SShanmugavel, MMarruthachalam. FusionofIRS-LISSIIIandPANimagesusingdifferent resolutionratios[C]. In:PaperPresentedatthe22ndAsianConferenceonRemoteSensing.2001.
    [50]PatSChavez. Comparisonofthreedifferentmethodstomergemultiresolutionandmultispectr aldata:LandsatTMandSPOTpanchromatic[J]. PE&RS1991,57(3):259-303.
    [51]张炳智,张继贤,张丽.土地利用动态遥感监测中多源遥感影像融合方法比较研究[J].测绘科学,2000(3):46-50.
    [52]李长伟,彭嘉雄.多源遥感图像的分层融合研究[J].华中科技大学学报(自然科学版),2002,30(5):25-27
    [53]Pohl C.& J. L. Van Genderen 1998, Multisensor Image Fusion in Remote Sensing:Concepts, Methods and Application, lnt[J]. Remot Sensing,19(5):823-854.
    [54]党安荣王晓栋等.ERDAS IMAGINE遥感图像处理方法[M].清华大学出版社
    [55]周成虎,等.遥感图像地学理解与分析[M].北京:科学出版社,2001
    [56]贾永红。数字图像处理[M]。武汉大学出版社。2003
    [57]朱述龙.快速近似主成分分析算法[J].遥感学报,1999,3:43-47.
    [58]高建国,郭君。矿产资源信息系统构建及应用[M]。云南出版集团公司云南科技出版社,2007
    [59]孙华,林辉,熊育久等。Spot5影像统计分析及最佳组合波段选择[D].遥感信息。2006,4
    [60]王雷.基于DEM的东川泥石流地质环境遥感研究[D].昆明理工大学。2008
    [61]荆凤,陈建平.矿化蚀变信息的遥感提取方法综述[J].遥感信息,2005,2:62265.
    [62]周成虎,骆剑承,刘庆生等。遥感影像地学理解与分析[M]。科学出版社。2001[2]:142-155
    [63]蒲静娟.遥感图像目视解译原理与方法[M].北京:中国科学技术出版社.1991[1]:82-85
    [64]高明星.东天山遥感影像线性构造提取及统计分析[D].新疆大学.2005
    [65]杨世瑜,王瑞雪.矿床遥感地质问题[M].云南:云南大学出版社,2003
    [66]遥感专辑,第一辑.矿物岩石的(可见)中红外光谱及应用[M].北京:地质出版社,1980.
    [67]张玉君,杨建民.基岩裸露区蚀变遥感信息的提取方法[J].国土资源遥感,1998,(2):46-53.
    [68]张玉君,曾朝铭,陈薇.ETM+(TM)蚀变遥感异常提取方法研究与应用—方法选择和技术流程[J].国土资源遥感,2003,(2):44—49.
    [69]马建文.利用TM数据快速提取含矿蚀变带方法研究[J].遥感学报,1997,1(3):208-212.
    [70]陈光火.中等程度植被覆盖区岩石蚀变信息提取技术及其应用[J].国土资源遥感,1992,3:55-60
    [71]甘甫平,王润生.遥感岩矿信息提取基础与技术方法研究[M].北京:地质出版社,2003
    [72]赵鹏大,池顺都.当今矿产勘查问题的思考[J].地球科学—中国地质大学学报,1998,23(1):70-74
    [73]陈毓川.当代矿产资源勘查评价的理论与方法[M].北京:地震出版社.1999
    [74]黄旭钊.利用MAPINFO综合分析多源地学信息进行矿产预测[J].地球科学—中国地质大学学报,2001,26(2):189-191
    [75]王世称,王於天.综合信息解译原理与矿产预测图编制方法[M].长春:吉林大学出版社,1989
    [76]王世称,陈永良,夏立显.综合信息矿产预测理论与方法[M].北京:科学出版社,2000
    [77]朱裕生.矿产资源评价方法导论[M].北京:地质出版社,1984
    [78]李建成.矿产资源定量预测方法综述[J].地质科技情报,1995,14(4):57-64
    [79]国家辉.桂西北超微粒浸染型金矿成矿地质条件及找矿模式[J].广西地质,1994,7(2):37-49
    [80]肖克炎.试论综合找矿模型[J].地质与勘探,1994,30(1):41-45
    [81]王全明,方一平.矿产资源调查评价中的GIS[J].中国地质,2001,28(4):38-44
    [82]卢作祥,范永香,刘辅臣.成矿规律和成矿预测学[M].武汉:中国地质大学出版社.1988
    [83]吴堑虹.利用GIS编制矿产预测图[J].地质与勘探,2000,36(3):48-50.
    [84]高建国.个旧矿区龙树脚矿段综合信息成矿预测与资源合理开发利用[M].昆明:云南科技出版社,2004.
    [85]杨世瑜,钟昆明等.斑岩金矿床快速定位预测研究—北衙斑岩型金矿床影像线环构造-构造地球化学快速定位预测[M].昆明:云南大学出版社,2006

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700