基于Landsat 8影像赤壁-嘉鱼地区岩性划分效果分析
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摘要
以鄂东南赤壁-嘉鱼地区为例,在缺少地表各岩石单元样品的情况下,对Landsat 8可见光近红外和短波红外(VNIRSWIR)波段反射率数据进行处理提取岩性信息。首先对VNIR-SWIR多波段反射率数据进行最佳指数因子(IOIF)运算,得出最佳波段组合band7-band5-band2,从其假彩色合成图像上只能识别少量岩性单元;为了减少高相关性波段之间的信息冗余度,并对波段信息进行集成,后对Landsat 8 VNIR-SWIR波段反射率数据采用主成分变换并进行彩色合成,能够有效增强志留系、侏罗系及第四系地质单元之间的影像差异,从而划分岩性界线。对比已有地质资料,认为提取结果可靠,能为野外地质工作提供基础信息。
Taking Chibi-Jiayu area in southeastern Hubei as an example, lithologic information was extracted from Landsat 8 visible near infrared and short wave infrared(VNIR-SWIR) band reflectance data in the absence of surface rock unit samples. Firstly, the optimal index factor(IOIF) of VNIR-SWIR multi-band reflectance data is calculated, and the optimal band combination band7-band5-band2 is obtained. Only a few lithologic units can be identified from its pseudo-color synthetic image. In order to reduce the information redundancy between high correlation bands and integrate band information, principal component transformation is used for Landsat 8 VNIR-SWIR band reflectance data. The color synthesis can effectively enhance the image differences among Silurian, Jurassic and Quaternary geological units, and thus divide lithologic boundaries. Compared with the existing geological data, it is believed that the extraction results are reliable and can provide basic information for field geological work.
Taking Chibi-Jiayu area in southeastern Hubei as an example, lithologic information was extracted from Landsat 8 visible near infrared and short wave infrared(VNIR-SWIR) band reflectance data in the absence of surface rock unit samples. Firstly, the optimal index factor(IOIF) of VNIR-SWIR multi-band reflectance data is calculated, and the optimal band combination band7-band5-band2 is obtained. Only a few lithologic units can be identified from its pseudo-color synthetic image. In order to reduce the information redundancy between high correlation bands and integrate band information, principal component transformation is used for Landsat 8 VNIR-SWIR band reflectance data. The color synthesis can effectively enhance the image differences among Silurian, Jurassic and Quaternary geological units, and thus divide lithologic boundaries. Compared with the existing geological data, it is believed that the extraction results are reliable and can provide basic information for field geological work.
引文
[1]侯德华，张立国，王硕，王金贵，程州.基于GF-2-影像西藏桑耶地区岩性-构造遥感解译[J].中国地质调查，2018,5(5):66-73.
[2]张焜，马世斌，李宗仁，刘世英.高分一号卫星数据遥感地质解译[J].遥感信息，2016,31(1):115-123.
[3]周灵洁，张正伟，程远，沈能平，张宗山，游富华.西昆仑北部地区铅锌铜矿带遥感构造蚀变信息提取与成矿预测[J].大地构造与成矿学，2011,5(4):603-611.
[4]王彪，陈利燕，王核，任广利，吴玉峰，黄朝阳，付王伟.遥感蚀变信息定量提取方法在成矿预测中的应用———以西昆仑塔什库尔干地区为例[J].大地构造与成矿学，2011,35(3):372-377.
[5] Salisbury J W, Mimms D L, Bender L V, Podwysocki M H,Jones O D. Analysis of Landsat 4 TM data for lithologic and image mapping purpose[C].//Barker J. Landsat 4Science Investigations Summary, Greenbelt. 1984.
[6]齐跃明，梁杏，万军伟. TM图像上断裂构造的识别及其地质应用———以安徽南部东西向断裂构造为例[J].华南地质与矿产，2003,(2):68-71.
[7]李昌国，张玉君.试用主分量分析方法提取澜沧江兰坪地区铜矿化蚀变遥感信息[J].国土资源遥感，1997.(1):20-30.
[8] Sultan M, Arvidson R E, Sturchio N C. Lithological mapping in arid regions with Landsat thematic mapper data:Meatiq dome, Egypt[J]. Geological Society of America Bulletin,1987, 9(6):748-762.
[9] Bernard E, Hubbard, James K, Crowley. Mineral mapping on the Chilean—Bolivian Altiplano using co-orbital ALI,ASTER and Hyperion imagery:Data dimensionality issues and solutions[J]. Remote Sensing of Environment, 2005,9:173-186.
[10]傅锦，韩晓青，张杰林，裴承凯.基于Hyperion数据的岩矿蚀变信息的特征峰提取法[J].世界核地质科学，2008,25(1):40-47.
[11]阚明哲，田庆久，张宗贵.新疆哈密三种典型蚀变矿物HyMap高光谱遥感信息提取[J].国土资源遥感，2005,63):37-40.
[12]姜小光，王长耀，王成.成像光谱数据的光谱信息特点及最佳波段选择———以北京顺义区为例[J].干旱区地理，2002,23(3):214-220.
[13] Chavez P S, Berlin G L, Sowers L B. Statistical methods for selection Landsat MSS ratios[J]. Journal of Applied Photographic Engineering, 1982, 8(1):23-30.
[2]张焜，马世斌，李宗仁，刘世英.高分一号卫星数据遥感地质解译[J].遥感信息，2016,31(1):115-123.
[3]周灵洁，张正伟，程远，沈能平，张宗山，游富华.西昆仑北部地区铅锌铜矿带遥感构造蚀变信息提取与成矿预测[J].大地构造与成矿学，2011,5(4):603-611.
[4]王彪，陈利燕，王核，任广利，吴玉峰，黄朝阳，付王伟.遥感蚀变信息定量提取方法在成矿预测中的应用———以西昆仑塔什库尔干地区为例[J].大地构造与成矿学，2011,35(3):372-377.
[5] Salisbury J W, Mimms D L, Bender L V, Podwysocki M H,Jones O D. Analysis of Landsat 4 TM data for lithologic and image mapping purpose[C].//Barker J. Landsat 4Science Investigations Summary, Greenbelt. 1984.
[6]齐跃明，梁杏，万军伟. TM图像上断裂构造的识别及其地质应用———以安徽南部东西向断裂构造为例[J].华南地质与矿产，2003,(2):68-71.
[7]李昌国，张玉君.试用主分量分析方法提取澜沧江兰坪地区铜矿化蚀变遥感信息[J].国土资源遥感，1997.(1):20-30.
[8] Sultan M, Arvidson R E, Sturchio N C. Lithological mapping in arid regions with Landsat thematic mapper data:Meatiq dome, Egypt[J]. Geological Society of America Bulletin,1987, 9(6):748-762.
[9] Bernard E, Hubbard, James K, Crowley. Mineral mapping on the Chilean—Bolivian Altiplano using co-orbital ALI,ASTER and Hyperion imagery:Data dimensionality issues and solutions[J]. Remote Sensing of Environment, 2005,9:173-186.
[10]傅锦，韩晓青，张杰林，裴承凯.基于Hyperion数据的岩矿蚀变信息的特征峰提取法[J].世界核地质科学，2008,25(1):40-47.
[11]阚明哲，田庆久，张宗贵.新疆哈密三种典型蚀变矿物HyMap高光谱遥感信息提取[J].国土资源遥感，2005,63):37-40.
[12]姜小光，王长耀，王成.成像光谱数据的光谱信息特点及最佳波段选择———以北京顺义区为例[J].干旱区地理，2002,23(3):214-220.
[13] Chavez P S, Berlin G L, Sowers L B. Statistical methods for selection Landsat MSS ratios[J]. Journal of Applied Photographic Engineering, 1982, 8(1):23-30.
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