PCA和布谷鸟算法优化SVM的遥感矿化蚀变信息提取
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摘要
为了进一步提高遥感矿化蚀变信息提取的精度,本文提出了一种基于主成分分析PCA (Principal Component Analysis)和布谷鸟算法优化支持向量机SVM (Support Vector Machine)的遥感矿化蚀变信息提取方法。首先,通过波段比值法增强研究区遥感图像中的矿化蚀变信息,并获得比值图像;然后,对比值图像进行主成分分析,进而提取训练样本;接着,利用SVM对训练样本进行训练,同时采用布谷鸟算法求取SVM的最优核参数及惩罚因子,构造最优SVM模型;最后,运用最优SVM模型完成矿化蚀变信息提取。选择青海省五龙沟地区为研究区,提取羟基及铁染蚀变信息。实验结果表明,与主成分分析法、基于光谱角法和SVM的方法、基于粒子群和SVM的方法及基于波段比值、PCA和粒子群优化SVM的方法等4种方法相比,本文方法获得的遥感矿化蚀变信息和已知矿点的吻合度最高,提取效果最好。
With the rapid development of the economy, the demand for mineral resources is growing, and the contradiction between supply and demand is increasing. The shortage of mineral resources has become one of the important factors that restrict national economic development. Therefore, research on how to efficiently and accurately explore mineral resources is a critical endeavor. Remote sensing mineralization alteration information extraction is an important application of remote sensing technology in geological exploration, which is of utmost significance to mineral exploration and evaluation. Owing to the influence of vegetation, cloud, and snow, alteration information from remote sensing mineralization is often superimposed with the complex geological background and exists only in the form of a weak signal in the background of the remote sensing image. Research on effective remote sensing mineralization alteration information extraction methods can provide the basis for the study of regional metallogenic prognosis and speed up the evaluation of mineral resources exploration, which helps promote the healthy and stable development of the local mining economy. To improve the accuracy of remote sensing mineralization alteration information extraction method, a remote sensing mineralization alteration information extraction method based on Principal Component Analysis(PCA) and Support Vector Machine(SVM) optimized by cuckoo algorithm is proposed in this study. First, the mineralization alteration information in the remote sensing image of the study area is enhanced by band ratio method, and the ratio images are obtained. Then PCA is applied to the ratio images of the study area. The hydroxyl principal components and iron staining principal components are selected, after which the training samples are extracted. Subsequently, the training samples are trained by SVM, while cuckoo algorithm is used to find the optimal kernel parameter and penalty factor of SVM. Thus,the optimal SVM model is determined. Finally, the optimal SVM model is used to accomplish the extraction of remote sensing mineralization alteration information in the study area. Wulonggou area of Qinghai Province, which is rich in mineral resources, is selected as the study area where the hydroxyl alteration information and iron alteration information are extracted. A detailed comparison among the proposed method and four methods proposed recently, namely, the PCA method, the method based on spectral angle mapper and SVM, the method based on particle swarm optimization and SVM, and the method based on band ratio, PCA, and SVM optimized by particle swarm optimization in terms of extraction effect and matching rate, is given in this paper. Experimental results show that by using the proposed method, the extracted information can comprehensively reflect the remote sensing mineralization alteration information of the study area. Moreover, the matching degree of hydroxyl alteration information and iron alteration information are 86.5% and 69.2%, respectively. Meanwhile, compared with the four methods, the proposed method can obtain the highest matching degree with the best extraction effect. The proposed remote sensing mineralization alteration information extraction method based on PCA and SVM optimized by cuckoo algorithm is an effective method that provides a new idea for mineral exploration and metallogenic prediction.
With the rapid development of the economy, the demand for mineral resources is growing, and the contradiction between supply and demand is increasing. The shortage of mineral resources has become one of the important factors that restrict national economic development. Therefore, research on how to efficiently and accurately explore mineral resources is a critical endeavor. Remote sensing mineralization alteration information extraction is an important application of remote sensing technology in geological exploration, which is of utmost significance to mineral exploration and evaluation. Owing to the influence of vegetation, cloud, and snow, alteration information from remote sensing mineralization is often superimposed with the complex geological background and exists only in the form of a weak signal in the background of the remote sensing image. Research on effective remote sensing mineralization alteration information extraction methods can provide the basis for the study of regional metallogenic prognosis and speed up the evaluation of mineral resources exploration, which helps promote the healthy and stable development of the local mining economy. To improve the accuracy of remote sensing mineralization alteration information extraction method, a remote sensing mineralization alteration information extraction method based on Principal Component Analysis(PCA) and Support Vector Machine(SVM) optimized by cuckoo algorithm is proposed in this study. First, the mineralization alteration information in the remote sensing image of the study area is enhanced by band ratio method, and the ratio images are obtained. Then PCA is applied to the ratio images of the study area. The hydroxyl principal components and iron staining principal components are selected, after which the training samples are extracted. Subsequently, the training samples are trained by SVM, while cuckoo algorithm is used to find the optimal kernel parameter and penalty factor of SVM. Thus,the optimal SVM model is determined. Finally, the optimal SVM model is used to accomplish the extraction of remote sensing mineralization alteration information in the study area. Wulonggou area of Qinghai Province, which is rich in mineral resources, is selected as the study area where the hydroxyl alteration information and iron alteration information are extracted. A detailed comparison among the proposed method and four methods proposed recently, namely, the PCA method, the method based on spectral angle mapper and SVM, the method based on particle swarm optimization and SVM, and the method based on band ratio, PCA, and SVM optimized by particle swarm optimization in terms of extraction effect and matching rate, is given in this paper. Experimental results show that by using the proposed method, the extracted information can comprehensively reflect the remote sensing mineralization alteration information of the study area. Moreover, the matching degree of hydroxyl alteration information and iron alteration information are 86.5% and 69.2%, respectively. Meanwhile, compared with the four methods, the proposed method can obtain the highest matching degree with the best extraction effect. The proposed remote sensing mineralization alteration information extraction method based on PCA and SVM optimized by cuckoo algorithm is an effective method that provides a new idea for mineral exploration and metallogenic prediction.
引文
Chen J P,Wang Q,Dong Q J and Cong Y.2009.Extraction of remote sensing alteration information in Lilotuohe,Qinghai Province.Earth Science-Journal of china University of Geosciences,34(2):314-318(陈建平,王倩,董庆吉,丛源.2009.青海沱沱河地区遥感蚀变信息提取.地球科学--中国地质大学学报,34(2):314-318)[DOI:10.3321/j.issn:1000-2383.2009.02.014]
Diao H,Zhang D,Di Y J,Wang Z,Wang H R and Xiong G Q.2011.The extraction of alteration anomalies from ASTER data based on principal component analysis and fractal model.Remote Sensing for Land and Resources(2):75-80(刁海,张达,狄永军,王振,王浩然,熊光强.2011.基于主成分分析和分形模型的ASTER蚀变异常信息提取.国土资源遥感(2):75-80)
Ding S F,Qi B J and Tan H Y.2011.An overview on theory and algorithm of support vector machines.Journal of University of Electronic Science and Technology of China,40(1):2-10(丁世飞,齐丙娟,谭红艳.2011.支持向量机理论与算法研究综述.电子科技大学学报,40(1):2-10)[DOI:10.3969/j.issn.1001-0548.2011.01.001]
Dong C J,Liu Y and Peng Y.2016.Improved cuckoo search algorithm applied to multi-objective optimization of crowd evacuation.Journal of System Simulation,28(5):1063-1069(董崇杰,刘毅,彭勇.2016.改进布谷鸟算法在人群疏散多目标优化中的应用.系统仿真学报,28(5):1063-1069)[DOI:10.16182/j.cnki.joss.2016.05.009]
Fu W J,Hong J Y and Zhu G C.2006.The extraction of mineralized and altered rock information from remote sensing image based on SVM.Remote Sensing for Land and Resources(2):16-19(傅文杰,洪金益,朱谷昌.2006.基于SVM遥感矿化蚀变信息提取研究.国土资源遥感(2):16-19)
Gao J G,Xue C J,Wu G G,Wang X H,Zhou G,Yang W P,Wang Xand Chen J.2008.Method of fast extracting alteration remote sensing abnormal information based on knowledge and prospecting application.Journal of Remote Sensing,12(1):186-192(高景刚,薛春纪,吴淦国,王晓虎,周刚,杨文平,王祥,陈静.2008.基于知识的蚀变遥感异常信息快速提取及找矿应用实践.遥感学报,12(1):186-192)[DOI:10.11834/jrs.20080124]
He K T,Gan F P and Wang Y J.2009.The extraction of geological micro-structure and altered rock information with high-resolution satellite images in a small range.Remote Sensing for Land and Resources(1):97-99(何凯涛,甘甫平,王永江.2009.高空间分辨率卫星遥感地质微构造及蚀变信息识别.国土资源遥感(1):97-99)
Hecker C,Van Der Meijde M,Van Der Werff H and Van der Meer FD.2008.Assessing the influence of reference spectra on synthetic SAM classification results.IEEE Transactions on Geoscience and Remote Sensing,46(12):4162-4172[DOI:10.1109/TGRS.2008.2001035]
Imbroane M A,Melenti C and Gorgan D.2007.Mineral explorations by Landsat image ratios//Proceedings of 2007 International Symposium on Symbolic and Numeric Algorithms for Scientific Computing.Timisoara:IEEE:335-340[DOI:10.1109/SYNASC.2007.52]
Lian Y X and Jiang Y B.2013.Extracting mineralized alteration information of iron and argillation based on remote sensing technology-taking the mining area of Makeng-Datian,Fujian Province as an example.Journal of East China Institute of Technology,32(3):384-389(连艺昕,姜勇彪.2013.基于遥感技术的铁染和泥化蚀变异常信息提取--以福建马坑-大田整装勘查区矿区为例.东华理工大学学报(社会科学版),32(3):384-389)
Liu L,Zhou J,Yin F and Feng M.2013.Alteration mineral mapping and ore prospecting based on ASTER data in Balikun,Xinjiang.Remote Sensing Technology and Application,28(4):556-561(刘磊,周军,尹芳,冯敏.2013.基于ASTER数据的巴里坤地区蚀变矿物填图及找矿.遥感技术与应用,28(4):556-561)[DOI:10.11873/j.issn.1004-0323.2013.4.556]
Mia M B,Nishijima J and Fujimitsu Y.2014.Exploration and monitoring geothermal activity using Landsat ETM+images:a case study at Aso volcanic area in Japan.Journal of Volcanology and Geothermal Research,275:14-21[DOI:10.1016/j.jvolgeores.2014.02.008]
Pour A B,Hashim M and Van Genderen J.2013.Detection of hydrothermal alteration zones in a tropical region using satellite remote sensing data:bau goldfield,Sarawak,Malaysia.Ore Geology Reviews,54:181-196[DOI:10.1016/j.oregeorev.2013.03.010]
Sadeghi B,Khalajmasoumi M,Afzal P,Moarefvand P,Yasrebi A B,Wetherelt A,Foster P and Ziazarifif A.2013.Using ETM+and ASTER sensors to identify iron occurrences in the Esfordi1:100,000 mapping sheet of Central Iran.Journal of African Earth Sciences,85:103-114[DOI:10.1016/j.jafrearsci.2013.05.003]
Shen L X,Liu L P,Su X X,Zhu Y and Zhao F.2008.Study on identification of altered wall-rock in areas of different vegetation coverages based on remote sensing.Geoscience,22(2):293-298(沈利霞,刘丽萍,苏新旭,祝艳,赵芳.2008.不同植被覆盖率地区遥感矿化蚀变提取研究.现代地质,22(2):293-298)[DOI:10.3969/j.issn.1000-8527.2008.02.017]
Tuba M,Subotic M and Stanarevic N.2011.Modified cuckoo search algorithm for unconstrained optimization problems//Proceedings of the 5th European Conference on European Computing Conference.Paris:ACM:263-268
Walton S,Hassan O,Morgan K and Brown M R.2011.Modified cuckoo search:a new gradient free optimisation algorithm.Chaos,Solitons and Fractals,44(9):710-718[DOI:10.1016/j.chaos.2011.06.004]
Wang D.2008.Research of Remote Sensing Ore-Finding Method Based on Particle Swarm Intelligence.Changsha:Central South University(王东.2008.基于粒子群智能的遥感找矿方法研究.长沙:中南大学[DOI:10.7666/d.y1538461])
Wang Z H and Zheng C Y.2010.Rocks/Minerals information extraction from EO-1 hyperion data base on SVM//Proceedings of 2010International Conference on Intelligent Computation Technology and Automation.Guangzhou:IEEE:229-232[DOI:10.1109/ICICTA.2010.341]
Wu H,Xu Y J,Fan G J and Meng P Y.2016.Using ETM+data for extraction of alteration information based on singular value decomposition:a case study of Wulonggou gold deposit,Qinghai.Geography and Geo-Information Science,32(2):40-45(吴浩,徐元进,范高晶,孟鹏燕.2016.奇异值分解在ETM+遥感蚀变信息提取中的应用--以青海省五龙沟金矿勘查区为例.地理与地理信息科学,32(2):40-45)[DOI:10.3969/j.issn.1672-0504.2016.02.008]
Xu Y J,Ma H C and Peng S Y.2014.Study on identification of altered rock in hyperspectral imagery using spectrum of field object.Ore Geology Reviews,56:584-595[DOI:10.1016/j.oregeorev.2013.07.004]
Xue H R,Zhang K H,Li B and Peng C H.2015.Fault diagnosis of transformer based on the cuckoo search and support vector machine.Power System Protection and Control,43(8):8-13(薛浩然,张珂珩,李斌,彭晨辉.2015.基于布谷鸟算法和支持向量机的变压器故障诊断.电力系统保护与控制,43(8):8-13)
Yang G P,Yu X C,Chen W and Liu W.2008.Hyperspectral remote sensing image classification based on kernel fisher discriminant analysis.Journal of Remote Sensing,12(4):579-585(杨国鹏,余旭初,陈伟,刘伟.2008.基于核Fisher判别分析的高光谱遥感影像分类.遥感学报,12(4):579-585)[DOI:10.11834/jrs.20080476]
Yang J J,Jiang Q G,Zhao J,Xu Y and Meng X C.2012.Standard mineral quantitative calculation based on the improved SVM and hyperspectral remote sensing.Journal of Jilin University(Earth Science Edition),42(3):864-871(杨佳佳,姜琦刚,赵静,徐言,孟翔冲.2012.基于改进的SVM技术和高光谱遥感的标准矿物定量计算.吉林大学学报(地球科学版),42(3):864-871)[DOI:10.3969/j.issn.1671-5888.2012.03.034]
Yang X S and Deb S.2009.Cuckoo search via Lévy flights//Proceedings of 2009 World Congress on Nature and Biologically Inspired Computing.Coimbatore:IEEE:210-214[DOI:10.1109/NABIC.2009.5393690]
Yi G H.2011.Corresponding Analysis Metallogenic Prognosis of Geochemical and Remote Sensing Anomaly at Wu Long Gou Gold Mineralized Concentrate District in East Kunlun Mountain.Chengdu:Chengdu University of Technology(易桂花.2011.东昆仑五龙沟金矿集中区化探异常与遥感异常响应及成矿预测.成都:成都理工大学)
Yu H,He H,Chang L and Sun W D.2014.Alteration information extraction from remote sensing imagery based on support vector machines and spectral energy level matching.Remote Sensing Information,29(2):74-78(于浩,何浩,常玲,孙卫东.2014.基于光谱能级匹配的支持向量机蚀变信息提取.遥感信息,29(2):74-78)[DOI:10.3969/j.issn.1000-3177.2014.02.013]
Zhang Y T,Zhang X D,Liu Z Z,Zhang Y J and Zhang H J.2012.The extraction of fault structure and wall rock alteration remote sensing information in Ningxia.Remote Sensing for Land and Resources(1):132-136(张永庭,张晓东,刘自增,张永杰,张慧娟.2012.宁夏区地质构造与围岩蚀变遥感信息提取.国土资源遥感(1):132-136)[DOI:10.6046/gtzyyg.2012.01.23]
Zhao X X,Qian J P,Qin S Q,Huang K C and Han S.2013.Remote sensing prospecting in high vegetation coverage area--a case study of the in Datuanbao copper ore deposit and its environs,Jiangcheng,Yunnan Province.Remote Sensing Technology and Application,28(5):879-889(赵小星,钱建平,覃顺桥,黄克宸,韩帅.2013.云南江城大团包铜矿及外围高植被区遥感找矿预测.遥感技术与应用,28(5):879-889)
Diao H,Zhang D,Di Y J,Wang Z,Wang H R and Xiong G Q.2011.The extraction of alteration anomalies from ASTER data based on principal component analysis and fractal model.Remote Sensing for Land and Resources(2):75-80(刁海,张达,狄永军,王振,王浩然,熊光强.2011.基于主成分分析和分形模型的ASTER蚀变异常信息提取.国土资源遥感(2):75-80)
Ding S F,Qi B J and Tan H Y.2011.An overview on theory and algorithm of support vector machines.Journal of University of Electronic Science and Technology of China,40(1):2-10(丁世飞,齐丙娟,谭红艳.2011.支持向量机理论与算法研究综述.电子科技大学学报,40(1):2-10)[DOI:10.3969/j.issn.1001-0548.2011.01.001]
Dong C J,Liu Y and Peng Y.2016.Improved cuckoo search algorithm applied to multi-objective optimization of crowd evacuation.Journal of System Simulation,28(5):1063-1069(董崇杰,刘毅,彭勇.2016.改进布谷鸟算法在人群疏散多目标优化中的应用.系统仿真学报,28(5):1063-1069)[DOI:10.16182/j.cnki.joss.2016.05.009]
Fu W J,Hong J Y and Zhu G C.2006.The extraction of mineralized and altered rock information from remote sensing image based on SVM.Remote Sensing for Land and Resources(2):16-19(傅文杰,洪金益,朱谷昌.2006.基于SVM遥感矿化蚀变信息提取研究.国土资源遥感(2):16-19)
Gao J G,Xue C J,Wu G G,Wang X H,Zhou G,Yang W P,Wang Xand Chen J.2008.Method of fast extracting alteration remote sensing abnormal information based on knowledge and prospecting application.Journal of Remote Sensing,12(1):186-192(高景刚,薛春纪,吴淦国,王晓虎,周刚,杨文平,王祥,陈静.2008.基于知识的蚀变遥感异常信息快速提取及找矿应用实践.遥感学报,12(1):186-192)[DOI:10.11834/jrs.20080124]
He K T,Gan F P and Wang Y J.2009.The extraction of geological micro-structure and altered rock information with high-resolution satellite images in a small range.Remote Sensing for Land and Resources(1):97-99(何凯涛,甘甫平,王永江.2009.高空间分辨率卫星遥感地质微构造及蚀变信息识别.国土资源遥感(1):97-99)
Hecker C,Van Der Meijde M,Van Der Werff H and Van der Meer FD.2008.Assessing the influence of reference spectra on synthetic SAM classification results.IEEE Transactions on Geoscience and Remote Sensing,46(12):4162-4172[DOI:10.1109/TGRS.2008.2001035]
Imbroane M A,Melenti C and Gorgan D.2007.Mineral explorations by Landsat image ratios//Proceedings of 2007 International Symposium on Symbolic and Numeric Algorithms for Scientific Computing.Timisoara:IEEE:335-340[DOI:10.1109/SYNASC.2007.52]
Lian Y X and Jiang Y B.2013.Extracting mineralized alteration information of iron and argillation based on remote sensing technology-taking the mining area of Makeng-Datian,Fujian Province as an example.Journal of East China Institute of Technology,32(3):384-389(连艺昕,姜勇彪.2013.基于遥感技术的铁染和泥化蚀变异常信息提取--以福建马坑-大田整装勘查区矿区为例.东华理工大学学报(社会科学版),32(3):384-389)
Liu L,Zhou J,Yin F and Feng M.2013.Alteration mineral mapping and ore prospecting based on ASTER data in Balikun,Xinjiang.Remote Sensing Technology and Application,28(4):556-561(刘磊,周军,尹芳,冯敏.2013.基于ASTER数据的巴里坤地区蚀变矿物填图及找矿.遥感技术与应用,28(4):556-561)[DOI:10.11873/j.issn.1004-0323.2013.4.556]
Mia M B,Nishijima J and Fujimitsu Y.2014.Exploration and monitoring geothermal activity using Landsat ETM+images:a case study at Aso volcanic area in Japan.Journal of Volcanology and Geothermal Research,275:14-21[DOI:10.1016/j.jvolgeores.2014.02.008]
Pour A B,Hashim M and Van Genderen J.2013.Detection of hydrothermal alteration zones in a tropical region using satellite remote sensing data:bau goldfield,Sarawak,Malaysia.Ore Geology Reviews,54:181-196[DOI:10.1016/j.oregeorev.2013.03.010]
Sadeghi B,Khalajmasoumi M,Afzal P,Moarefvand P,Yasrebi A B,Wetherelt A,Foster P and Ziazarifif A.2013.Using ETM+and ASTER sensors to identify iron occurrences in the Esfordi1:100,000 mapping sheet of Central Iran.Journal of African Earth Sciences,85:103-114[DOI:10.1016/j.jafrearsci.2013.05.003]
Shen L X,Liu L P,Su X X,Zhu Y and Zhao F.2008.Study on identification of altered wall-rock in areas of different vegetation coverages based on remote sensing.Geoscience,22(2):293-298(沈利霞,刘丽萍,苏新旭,祝艳,赵芳.2008.不同植被覆盖率地区遥感矿化蚀变提取研究.现代地质,22(2):293-298)[DOI:10.3969/j.issn.1000-8527.2008.02.017]
Tuba M,Subotic M and Stanarevic N.2011.Modified cuckoo search algorithm for unconstrained optimization problems//Proceedings of the 5th European Conference on European Computing Conference.Paris:ACM:263-268
Walton S,Hassan O,Morgan K and Brown M R.2011.Modified cuckoo search:a new gradient free optimisation algorithm.Chaos,Solitons and Fractals,44(9):710-718[DOI:10.1016/j.chaos.2011.06.004]
Wang D.2008.Research of Remote Sensing Ore-Finding Method Based on Particle Swarm Intelligence.Changsha:Central South University(王东.2008.基于粒子群智能的遥感找矿方法研究.长沙:中南大学[DOI:10.7666/d.y1538461])
Wang Z H and Zheng C Y.2010.Rocks/Minerals information extraction from EO-1 hyperion data base on SVM//Proceedings of 2010International Conference on Intelligent Computation Technology and Automation.Guangzhou:IEEE:229-232[DOI:10.1109/ICICTA.2010.341]
Wu H,Xu Y J,Fan G J and Meng P Y.2016.Using ETM+data for extraction of alteration information based on singular value decomposition:a case study of Wulonggou gold deposit,Qinghai.Geography and Geo-Information Science,32(2):40-45(吴浩,徐元进,范高晶,孟鹏燕.2016.奇异值分解在ETM+遥感蚀变信息提取中的应用--以青海省五龙沟金矿勘查区为例.地理与地理信息科学,32(2):40-45)[DOI:10.3969/j.issn.1672-0504.2016.02.008]
Xu Y J,Ma H C and Peng S Y.2014.Study on identification of altered rock in hyperspectral imagery using spectrum of field object.Ore Geology Reviews,56:584-595[DOI:10.1016/j.oregeorev.2013.07.004]
Xue H R,Zhang K H,Li B and Peng C H.2015.Fault diagnosis of transformer based on the cuckoo search and support vector machine.Power System Protection and Control,43(8):8-13(薛浩然,张珂珩,李斌,彭晨辉.2015.基于布谷鸟算法和支持向量机的变压器故障诊断.电力系统保护与控制,43(8):8-13)
Yang G P,Yu X C,Chen W and Liu W.2008.Hyperspectral remote sensing image classification based on kernel fisher discriminant analysis.Journal of Remote Sensing,12(4):579-585(杨国鹏,余旭初,陈伟,刘伟.2008.基于核Fisher判别分析的高光谱遥感影像分类.遥感学报,12(4):579-585)[DOI:10.11834/jrs.20080476]
Yang J J,Jiang Q G,Zhao J,Xu Y and Meng X C.2012.Standard mineral quantitative calculation based on the improved SVM and hyperspectral remote sensing.Journal of Jilin University(Earth Science Edition),42(3):864-871(杨佳佳,姜琦刚,赵静,徐言,孟翔冲.2012.基于改进的SVM技术和高光谱遥感的标准矿物定量计算.吉林大学学报(地球科学版),42(3):864-871)[DOI:10.3969/j.issn.1671-5888.2012.03.034]
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