基于光谱磁化率模型的黄土剖面地层划分
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摘要
黄土剖面地层划分对于古地震研究具有重要意义,当前黄土地层的精细划分是一个薄弱环节。磁化率是土壤和沉积物的一个重要参数,能反映一定的沉积环境变化,常用来作为地层层序划分的标记。但离散的磁化率在反映黄土剖面地层结构空间展布特征时,会出现以点带面、以偏概全的问题。本研究选取平原区一处剖面为例,利用高光谱遥感具有图谱合一,光谱分辨率高,可以定量反演地表物理化学参数,分析地表物理化学过程的特点,探索建立光谱与反映地层韵律变化的磁化率之间的光谱模型,并将其应用到黄土剖面上,进行黄土地层结构特征分析。研究结果表明,基于光谱特征建立的磁化率模型精度较高(R~2﹥0.95),其得到的剖面磁化率强度分布图较好地展示了地层结构空间展布特征,为黄土剖面地层划分提供了依据。
Invisible fault identifying in loess area is a difficult problem in active fault study in northern China.Detailed stratigraphic division of loess area by the naked eye is very difficult due to the insignificant difference of the granularities and the colors,which would affect the identification of the obscured fault and paleo-seismic event. Spectral technique has been used for magnetic susceptibility estimation. Magnetic susceptibility( MS) has been considered to be a measure of the degree of pedogenic activity and excellent proxies for terrestrial climatic fluctuations. In this study,multiple linear regression was used to build MS estimation models based on the spectral features. A model was built and was applied to hyperspectral image. Test of datasets indicates that this model is very successful. The applying of this model to hyperspectral image shows that the intensity distribution of MS could be used for stratigraphic division.
Invisible fault identifying in loess area is a difficult problem in active fault study in northern China.Detailed stratigraphic division of loess area by the naked eye is very difficult due to the insignificant difference of the granularities and the colors,which would affect the identification of the obscured fault and paleo-seismic event. Spectral technique has been used for magnetic susceptibility estimation. Magnetic susceptibility( MS) has been considered to be a measure of the degree of pedogenic activity and excellent proxies for terrestrial climatic fluctuations. In this study,multiple linear regression was used to build MS estimation models based on the spectral features. A model was built and was applied to hyperspectral image. Test of datasets indicates that this model is very successful. The applying of this model to hyperspectral image shows that the intensity distribution of MS could be used for stratigraphic division.
引文
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[10]Deaton B C,Balsam W L.Visible spectroscopy:A rapid method for determining hematite and goethite concentration in geological materials[J].Journal of Sedimentary Petorology,1991,61(4):628-632.
[11]Ji J F,Balsam W,Chen J,et al.Rapid and quantitative measurement of hematite and goethite in the Chinese loess-epaleosol sequence by diffuse reflectance spectroscopy[J].Clays and Clay Minerals,2002,50(2):208-216.
[12]Scheinost A C,Chavernas A,Barrón V,et al.Use and limitation of second-derivative diffuse reflectance spectroscopy in the visible to near-infrared range to identify and quantify Fe oxide minerals in soils[J].Clays and Clay Minerals,1998,46(5):528-536.
[13]Smith M J,Stevens T,Mac Arthur A,et al.Characterising Chinese loess stratigraphy and past monsoon variation using field spectroscopy[J].Quaternary International,2011,234(1/2):146-158
[14]Hunt G R,Salisbury J W,Lenhoff C J.Visible and near-infrared spectra of minerals and rocks:III.Oxides and hydroxides[J].Modern Geology,1971,2:195-205.
[15]Cui J,Yan B K,Wang R S,et al.Regional-scale mineral mapping using ASTER VNIR/SWIR data and validation of reflectance and mineral map products using airborne hyperspectral CASI/SASI data[J].International Journal of Applied Earth Observation and Geoinformation,2014,33:127-141.
[16]Kruse F A,Lefkoff A B,Boardman J W,et al.The spectral image processing system(SIPS)-interactive visualization and analysis of imaging spectrometer data[J].Remote Sensing of Environment,1993,44(2/3):145-163.
[2]Balsam W,Ji J F,Chen J.Climatic interpretation of the Luochuan and Lingtai loess sections,China,based on changing iron oxide mineralogy and magnetic susceptibility[J].Earth and Planetary Science Letters,2004,223(3/4):335-348.
[3]Chen J,Ji J F,Balsam W,et al.Characterization of the Chinese loess-paleosol stratigraphy by whiteness measurement[J].Palaeogeography,Palaeoclimatology,Palaeoecology,2002,183(3/4):287-297.
[4]Liu X M,Hesse P,Rolph T.Origin of maghaemite in Chinese loess deposits:Aeolian or pedogenic?[J].Physics of the Earth and Planetary Interiors,1999,112(3/4):191-201.
[5]Maher B A,Thompson R.Mineral magnetic record of the Chinese loess and paleosols[J].Geology,1991,19(1):3-6.
[6]Maher B A.Magnetic properties of modern soils and Quaternary loessic paleosols:Paleoclimatic implications[J].Palaeogeography,Palaeoclimatology,Palaeoecology,1998,137(1/2):25-54.
[7]Zhou L P,Oldfield F,Wintle A G,et al.Partly pedogenic origin of magnetic variations in Chinese loess[J].Nature,1990,346(6286):737-739.
[8]季峻峰,陈骏,刘连文,等.洛川黄土中绿泥石的化学风化与磁化率增强[J].自然科学进展,1999,9(7):619-623.Ji J F,Chen J,Liu L W,et al.Chemical weathering of chlorite and enhancement of magnetic susceptibility in Luochuan Loess[J].Progress in Natural Science,1999,9(7):619-623.
[9]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,2004:43-47.Gan F P,Wang R S.Basis Theory and Technical Methods Study of Remote Sensing Rock and Mineral Information Extraction[M].Beijing:Geological Publishing House,2004:43-47.
[10]Deaton B C,Balsam W L.Visible spectroscopy:A rapid method for determining hematite and goethite concentration in geological materials[J].Journal of Sedimentary Petorology,1991,61(4):628-632.
[11]Ji J F,Balsam W,Chen J,et al.Rapid and quantitative measurement of hematite and goethite in the Chinese loess-epaleosol sequence by diffuse reflectance spectroscopy[J].Clays and Clay Minerals,2002,50(2):208-216.
[12]Scheinost A C,Chavernas A,Barrón V,et al.Use and limitation of second-derivative diffuse reflectance spectroscopy in the visible to near-infrared range to identify and quantify Fe oxide minerals in soils[J].Clays and Clay Minerals,1998,46(5):528-536.
[13]Smith M J,Stevens T,Mac Arthur A,et al.Characterising Chinese loess stratigraphy and past monsoon variation using field spectroscopy[J].Quaternary International,2011,234(1/2):146-158
[14]Hunt G R,Salisbury J W,Lenhoff C J.Visible and near-infrared spectra of minerals and rocks:III.Oxides and hydroxides[J].Modern Geology,1971,2:195-205.
[15]Cui J,Yan B K,Wang R S,et al.Regional-scale mineral mapping using ASTER VNIR/SWIR data and validation of reflectance and mineral map products using airborne hyperspectral CASI/SASI data[J].International Journal of Applied Earth Observation and Geoinformation,2014,33:127-141.
[16]Kruse F A,Lefkoff A B,Boardman J W,et al.The spectral image processing system(SIPS)-interactive visualization and analysis of imaging spectrometer data[J].Remote Sensing of Environment,1993,44(2/3):145-163.