A study on the potential of satellite image-derived hyperspectral signatures to assess the grades of iron ore deposits

This paper present the results of a study made to assess the grades of iron ore deposits in parts of Noamundi area using the hyperspectral image data (EO-1 Hyperion). The study involves hyperspectral image data, preprocessing (removal of atmospheric effects), spectral curve generation from the image, extraction of certain spectral parameters and spectral data analysis. Atmospheric correction was carried out by using algorithms involving atmospheric analysis of spectral hyper-cubes and Quick Atmospheric Correction modules. Spectral curves generated for the pixels that contain iron ores resemble the spectral signature of iron ores, i.e., very strong absorption at 850–900nm region is observed. The strength of the absorption varies spatially at different pixels. Hence, spectral parameters such as radius of curvature of NIR absorption trough (750–1000nm), position of NIR absorption trough and distance from a reference(100% reflectance) line have been derived for all the image-derived spectra and were compared with the concentration of iron in the ore samples of mines. Empirical models were generated by relating the image-derived spectral parameters of iron ore locations and geochemistry of the samples collected from the same location which shows a reasonable match. Strong negative correlation is seen between the radius of curvature of the NIR absorption trough and concentration of iron with a R² value of 0.809. The position of the NIR absorption trough is seen to shift towards longer wavelengths with decreasing iron content and the distance from the reference line increases with increasing iron content. Thus, this study indicates that it is feasible to discriminate the grades of iron ores from the spectral parameters derived from Hyperspectral satellite images.     

花岗伟晶岩型锂矿热红外反射光谱特征及锂元素定量反演研究

运用热红外反射光谱技术建立花岗伟晶岩型锂矿识别方法,可以用来对目标靶区开展含矿性快速评价工作.锂辉石在热红外波段主要存在四个吸收峰,波长位置分别位于8 600 nm,9 150 nm,9 350 nm和11 670 nm处附近,其中11 670 nm处的吸收峰是锂辉石矿物的特征吸收峰,吸收深度为0.021 9～0.04...     

辽宁兴城地区岩石光谱测试及特征分析

在辽宁兴城野外实习基地采用ASD光谱仪完成不同岩石样品光谱测试的基础上, 分析了不同类型、不同地质时代的岩浆岩和沉积岩, 及其风化面和新鲜面的光谱曲线特征。兴城野外不同岩浆岩与沉积岩光谱曲线形态相似, 新鲜面和风化面的特征光谱吸收位置相差不大, 但新鲜面的反射率普遍高于风化面的反射率;岩浆岩和沉积岩样品一般在波长为900 nm左右存在铁离子吸收谷;除了在1 400 nm和1 900 nm处有水汽吸收带外, 岩浆岩和沉积岩样品在2 200 nm左右还存在强吸收谷, 而灰岩在2 300 nm左右有比较高的吸收谷, 这也是利用实测光谱进行岩性分类的理论基础。但是, 不同地质年代下的岩石光谱曲线变化并无规律, 更多地与岩石结构、成分和环境因素等相关。这样, 岩石光谱测试及其特征分析可满足研究区岩性识别、矿化蚀变信息提取的需要。     

Spectral characterization of soil and coal contamination on snow reflectance using hyperspectral analysis

Snow is a highly reflecting object found naturally on the Earth and its albedo is highly influenced by the amount and type of contamination. In the present study, two major types of contaminants (soil and coal) have been used to understand their effects on snow reflectance in the Himalayan region. These contaminants were used in two categories quantitatively – addition in large quantity and addition in small quantity. Snow reflectance data were collected between 350 and 2500 nm spectral ranges and binned at 10 nm interval by averaging. The experiment was designed to gather the field information in controlled conditions, and radiometric observations were collected. First derivative, band absorption depth, asymmetry, percentage change in reflectance and albedo in optical region were selected to identify and discriminate the type of contamination. Band absorption depth has shown a subtle increasing pattern for soil contamination, however, it was significant for small amounts of coal contamination. The absorption peak asymmetry was not significant for soil contamination but showed a nature towards left asymmetry for coal. The width of absorption feature at 1025 nm was not significant for both the contaminations. The percentage change in reflectance was quite high for small amount of coal contamination rather than soil contamination, however, a shift of peak was observed in soil-contaminated snow which was not present in coal contamination. The albedo drops exponentially for coal contamination rather than soil contamination.     

Reflectance spectroscopy and remote sensing data for finding sulfide-bearing alteration zones and mapping geology in Gilgit-Baltistan,Pakistan

Gilgit-Baltistan region is covering the northern most part of Pakistan where the rocks of the Kohistan-Ladakh island arc and Karakoram plate are exposed. The area has greater potential for precious and base metals deposits which are needed to be explored through spectroscopy and remote sensing techniques. Minerals and rocks can nowadays be identified through the measurement of their absorption and reflectance features by spectroscopic analysis. Spectral reflectance analysis is also very important in selecting the appropriate spectral bands for remote-sensing data analysis of unknown or inaccessible areas. In this study, reflectance spectra in the spectral range of 0.35–2.5 μm of different types of unaltered and altered rocks found in the Machulu and Astor areas of northern Pakistan were obtained using an ASD spectroradiometer. The fresh rock samples showed low spectral reflectance as compared to the altered rock samples. The minerals jarosite, goethite, and hematite showed depth of absorption minima in the range of 0.4–1.15 μm due to the presence of iron (Fe), while jarosite and limonite showed absorption depth at 2.2 μm due to the presence of hydroxyl ions (OH^¯). The clay minerals montmorillonite and illite showed absorption depth at 1.93 and 2.1 μm, respectively. Muscovite showed depth of absorption minima at 1.4 and 1.9 μm in some samples. Calcite showed deep absorption minima at 2.32 μm, while anorthite showed absorption features at 1.4, 1.9, 2.24, and 2.33 μm. Olivine showed a slight depressed absorption feature at 1.07 μm. The copper-bearing phases malachite, chrysocolla, and azurite showed, respectively, a broad absorption feature in the range of 0.6–0.9 μm, a small absorption at 1.4 μm, and a deep absorption at 1.93 μm. The unmineralized samples exhibited high reflectance in the wavelength ranges of 0.6–0.8, 1.6–1.9, 2.0–2.3, 2.1–2.25, and 2.4–2.5 μm, respectively, while the mineralized samples showed reflectance bands in the wavelength ranges of 0.4–0.6, 1.3–1.8, and 2.1–2.2 μm. On this basis, the band ratio combinations 7/5–4/3–6/3 and 7/5–6/3–4/3 of Landsat 8 and 4/7–4/3–2/1 for ASTER data were found to be very effective in the lithological differentiation of major rock units.     

Characterisation of carbonate minerals from hyperspectral TIR scanning using features at 14 000 and 11 300 nm

Rapid characterisation of carbonate phases in hyperspectral reflectance spectra acquired from drill core material has important implications for mineral exploration and resource modelling. Major infrared active features of carbonates lie in the thermal region around 6500 nm, 11 300 nm and 14 000 nm, with the latter two features being most useful for differentiating mineral species. A scatter diagram of the wavelength of the 14 000 nm feature vs that of the 11 300 nm feature, powerfully differentiates carbonates. Although the wavelength of the 11 300 nm peak is easily measured, the 14 000 nm trough and peak are commonly weak and their wavelengths can confidently be used only after filtering the spectra, e.g. selecting only those with the trough and peak separated by 175–230 nm, typical of common carbonates. The method is demonstrated with drillhole 120R from the Rosebery polymetallic VHMS deposit in western Tasmania, which has been scanned with the HyLogger-3 system. A 14 000–11 300 plot shows a high degree of clustering of the drillhole 120R data close to the library spectra of calcite, dolomite, Fe-dolomite, ankerite, kutnohorite, rhodochrosite, Fe-rhodochrosite and siderite. The interpreted compositions of the carbonate spectral populations strongly correlate with the chemical populations of 144 analysed carbonates and provide a highly resolved spatial framework for interpreting carbonate alteration.     

Reflectance spectroradiometry applied to a semi-quantitative analysis of the mineralogy of the N4ws deposit,Carajás Mineral Province,Pará, Brazil

Quantifying the abundance and physicochemical properties of minerals using reflectance spectroradiometry in the visible, near infrared and shortwave infrared (400–2500 nm) regions is an important tool in mineral exploration. In this study, the reflectance spectra of drill cores from the world-class N4WS iron deposit located in the Carajás Mineral Province, Brazil, were obtained. These spectra were validated using X-ray fluorescence (XRF) geochemical analyses and thin sections. The reflectance spectra were collected using a FieldSpec 3 spectroradiometer (ASD, Boulder, Colorado, USA) in 10 drill cores. The mineralogy of the deposit is mainly hematite, with lesser amounts of magnetite, goethite, quartz, kaolinite, gibbsite, smectite, talc, carbonate and chlorite. The mineralogy of the iron deposit was extracted from the spectral data using the geometry (depth and wavelength) of absorption features across the reflectance spectrum removed from the continuum. The depth of the absorption features is proportional to the mineral abundance, and the wavelength is proportional to the mineral chemical composition. The diagnostic absorption features of each mineral were used to determine the mineral abundance and composition. The final products include the abundance of iron (hydro) oxide (11.6% root-mean-square error [RMSE] Fe₂O₃); abundance of aluminous clays (RMSE 6% Al₂O₃); abundance of talc (8% RMSE MgO); identification of clay type (kaolinite, montmorillonite or gibbsite); composition of carbonate (dolomite vs. calcite); and composition of chlorite (Mg vs. Fe). The mineral abundance and composition results provided an effective characterisation of the ore, protore and host rocks and showed variations within the ore body.     

碳酸盐岩的反射光谱特征的研究及应用

在室内对新疆塔里木盆地西北缘柯坪地区碳酸盐岩的反射光谱进行了测量。分析结果表明：碳酸盐岩的特征吸收谱带位于２３００～２３５０ｎｍ，随着碳酸盐岩中Ｍｇ２＋含量的增加，其特征吸收谱带的中心波长位置具有向短波长方向移动的特点；同时，随着碳酸盐岩中碳酸盐矿物含量的增加，其特征吸收谱带的深度（Ｄ）也有增大的趋势，并且岩石的平均反射率（Ｒ）也随着增高。根据这些特征可以判定碳酸盐岩的岩石类型及碳酸盐矿物的相对含量     

Estimation of surface iron oxide abundance with suppression of grain size and topography effects

Mineral forms of iron oxide, such as hematite, goethite and jarosite, are important because they are widely distributed at the Earth’s surface and because they are used as indicators for mineral exploration. Iron oxide abundance in rocks containing these minerals can be estimated from the absorption depth at wavelengths of around 900 nm in a reflectance spectrum, but this depth is also affected by extraneous factors such as grain size and topography. This paper investigated the effect of grain size on reflectance spectra and proposed a method for estimating iron oxide abundance in surface rocks by using remotely sensed data with suppression of the effects of grain size and topography. Reflectance spectra were measured in a laboratory from rock powder samples of different grain sizes containing iron oxide minerals. While the reflectance increased with decreasing grain size, the presence of ferric iron caused the absorption depth to be almost constant at around 900 nm, irrespective of the chemical composition of the sample. In addition, the difference between the reflectance at 550 nm and 760 nm (Slope) was a function of grain size. Iron oxide abundance can be estimated accurately by MCR-900D, which is the maximum absorption depth at the absorption center after the effect of grain size and topography was suppressed by Slope and the continuum-removal method, which takes the ratio between the original spectrum and its continuum, respectively. Correlation of MCR-900D results with datasets of actual spectral and chemical iron oxide laboratory measurements revealed that the mineral forms also need to be considered. MCR-900D results were significantly correlated with rock samples classified as containing different forms of iron oxide minerals (hematite, goethite and jarosite). Finally, MCR-900D was applied to an AVIRIS dataset for the Cuprite site in Nevada, USA. The results represented the enrichment zones of iron oxide within hydrothermally altered areas.     

Determination of metamorphic grade in siliceous muscovite-bearing rocks in Madagascar using reflectance spectroscopy

Visible short-wave infrared laboratory reflectance spectra of quartzites and micaschists from the Precambrian basement of central-western Madagascar are dominated by the muscovite spectrum. The spectra were measured from rock samples collected along an E–W traverse across a metamorphic sequence recording progressively higher metamorphic grades. The wavelength of the Al–OH band around 2200 nm decreased westward and was inversely correlated with Al^VI content of muscovite in rocks showing the same nonlimiting assemblage. This shift is correlated also with an increase of band intensity, which is attributed to the progressive increase of metamorphic grade. All of these variations in rock spectral properties can be detected by the high spectral resolution MIVIS and AVIRIS sensors, as well as by the lower resolution TM sensor.     

南方冬季湿雪的光谱特征分析

使用FieldSpec4便携式地物光谱仪获取了南京地区冬季湿雪的光谱数据, 并从太阳高度角、坡度、坡向、下垫面及混合雪几个方面进行了分析. 结果表明: 积雪的反射率在可见光区变化平稳, 在近红外区下降迅速, 1 020 nm、1 250 nm附近是积雪反射率的吸收区; 湿雪状态下, 太阳高度角增大的同时积雪反射率逐渐降低, 而在水湿雪状态下太阳高度角对反射率影响减弱, 积雪含水率成为其变化的主要影响因素; 积雪反射率随着坡度的增大而增大; 积雪在朝阳坡的反射率远高于背阴坡, 背阴坡积雪反射率在可见光谱区受影响较大; 当积雪厚度达到一定值后下垫面的差异对反射率影响有限, 否则会对反射率产生较大影响; 在可见光波段纯雪反射率最高, 近红外波段植被/积雪混合反射率最高, 林下雪的光谱反射率较低. 南京地区湿雪光谱测量和分析对了解南方湿雪光谱特性和变化规律, 以及对于积雪定量遥感及其参数反演具有重要意义.     

基于ASTER VNIR-SWIR多光谱遥感数据识别与提取干旱地区岩性信息——以西南天山柯坪隆起东部为例

ASTER多光谱遥感数据目前可以用于岩石矿物资源信息的识别和提取。本研究尝试利用ASTER可见光近红外(VNIR)和短波红外(SWIR)的多光谱遥感数据提取干旱地区的岩石与矿物信息。基于新疆天山西南缘柯坪隆起东部不同地层单元岩石的化学组成和矿物成份以及VNIR-SWIR谱域光谱吸收特征的分析,我们采用相关吸收波段深度(RBD)和波段比值(BR)方法对研究区的多光谱遥感数据进行图像处理,有效区分和识别了白云岩、石灰岩、砂岩以及阿克苏群的蓝片岩—绿片岩和砂质片岩。白云岩的CO_3~(2-)吸收谱带中心波长位于2.32μm,与灰岩的CO_3~(2-)吸收谱带中心波长位置2.35μm相比,具有向短波长方向移动的特点,据此可以利用RBD7、RBD8分别有效的识别白云岩和灰岩;长英质岩石显示Al-OH和Fe~(3+)VNIR-SWIR吸收特征,而基性-超基性岩石显示Fe~(2+)和Fe、Mg-OH特征,利用不同的铁价态和次要矿物可以区分它们:ASTER band2/band1代表了含Fe~(3+)矿物分布信息、ASTER band5/band4代表了含Fe~(2+)矿物分布信息、RBD6可以估计Al-OH矿物的丰度;砂质/泥质片岩含较多的多硅白云母、绿泥石、黑硬绿泥石以及风化后表面覆盖的其它粘土矿物,在2.21μm(band6)存在有特征的吸收谱带,并且在1.65μm(band 4)具有较高的反射率,而蓝片/绿片岩在2.21μm(band 6)反射率较高,不具有明显特征吸收谱带,同时其在1.65μm(band 4)反射率较低,因此蓝片/绿片岩ASTER band4/band6比值低。应用ASTER band4/band6波段比值可以有效的区分开砂质/泥质片岩与蓝片岩/绿片岩。     

Constraining the colouration mechanisms of Cretaceous Oceanic Red Beds using diffuse reflectance spectroscopy

We have used diffuse reflectance spectroscopy to investigate the colouration mechanisms of hematite in Cretaceous Oceanic Red Beds (CORBs). Data for samples of CORBs from the Chuangde section in Tibet, Vispi Quarry section in Italy, and Core 12X of Ocean Drilling Program Hole 1049C in the North Atlantic were compared with calibration datasets obtained for hematite in different crystalline forms (kidney and specular hematite) and calcite matrix. Spectra for hematite in either pure form or in calibration datasets show that the centre of the reflection peak shifts to a longer wavelength and depth (D) decreases as the crystallinity of the hematite increases. Compared with specular hematite, the presence of just 0.5% of kidney hematite can cause a much deeper absorption peak and greater redness value, which indicates that kidney hematite has a higher colouration capacity than specular hematite. However, both kidney and specular hematite exhibit a good correlation between the redness value for each calibration dataset and the absorption peak depth. In all three studied sections, hematite is the main iron oxide mineral responsible for colouration. Spectral features such as absorption peak depth and peak centre reveal that hematite crystallinity gradually decreases from red shale to limestone to marl. Based on a spectral comparison of red shale in the Chuangde section before and after citrate–bicarbonate–dithionite (CBD) treatment, we found that two forms of hematite are present: a fine-grained and dispersed form, and a detrital form. The former is relatively poorly crystalline hematite, which has a much stronger colouration capacity than the detrital form. In the Vispi Quarry section and Core 12X of ODP Hole 1049C, a good correlation between the absorption peak depth of hematite and redness value indicates that the red colouration is caused by hematite of similar crystallinity in each section.     

基于ASTER VNIR SWIR多光谱遥感数据识别与提取干旱地区岩性信息——以西南天山柯坪隆起东部为例

ASTER多光谱遥感数据目前可以用于岩石矿物资源信息的识别和提取。本研究尝试利用ASTER 可见光近红外（VNIR）和短波红外（SWIR）的多光谱遥感数据提取干旱地区的岩石与矿物信息。基于新疆天山西南缘柯坪隆起东部不同地层单元岩石的化学组成和矿物成份以及VNIR SWIR谱域光谱吸收特征的分析,我们采用相关吸收波段深度（RBD）和波段比值（BR）方法对研究区的多光谱遥感数据进行图像处理,有效区分和识别了白云岩、石灰岩、砂岩以及阿克苏群的蓝片岩—绿片岩和砂质片岩。白云岩的CO2-3吸收谱带中心波长位于232〖KG*3〗μm,与灰岩的CO2-3 吸收谱带中心波长位置235 μm相比,具有向短波长方向移动的特点,据此可以利用RBD7、RBD8分别有效的识别白云岩和灰岩; 长英质岩石显示Al OH和Fe3+ VNIR SWIR吸收特征,而基性 超基性岩石显示Fe2+ 和Fe、Mg OH特征,利用不同的铁价态和次要矿物可以区分它们：ASTER band2/band1代表了含Fe3+ 矿物分布信息、ASTER band5/band4代表了含Fe2+ 矿物分布信息、RBD6可以估计Al OH矿物的丰度; 砂质/泥质片岩含较多的多硅白云母、绿泥石、黑硬绿泥石以及风化后表面覆盖的其它粘土矿物,在221 μm（band 6）存在有特征的吸收谱带,并且在165 μm（band 4）具有较高的反射率,而蓝片/绿片岩在221 μm（band 6）反射率较高,不具有明显特征吸收谱带,同时其在165 μm（band 4）反射率较低,因此蓝片/绿片岩ASTER band4/band6 比值低。应用ASTER band4/band6波段比值可以有效的区分开砂质/泥质片岩与蓝片岩/绿片岩。     

Two GUIs-based analysis tool for spectroradiometer data pre-processing

A new graphical user interface (GUI) for pre-processing reflectance spectra, built using MATLAB and expressly designed for the ASD FieldSpec® spectroradiometer, was developed to solve problems that generally affect experimental ASD data. The GUI is characterised by an easily readable, graphic visualisation of spectra, from which the absorption band depth (ABD) can be obtained for a selected wavelength. The output format of the ASD data is a binary file with an .asd extension. The binary file, that provides a single spectrum, can be processed using a software functionality, by means of a GUI, that allows to select one or more binary files to produce a spectral library in a unique .txt file. The spectral reflectance is re-calibrated with the “convex-hull” methodology to eliminate the convex shape, which is typical of reflectance spectra. Different examples of the use of the new GUI are provided.     

Using hyperspectral reflectance to detect different soil erosion status in the Subtropical Hilly Region of Southern China: a case study of Changting, Fujian Province

Hyperspectral reflectance is widely used for determining important properties of soil erosion. However, there have been few studies which focus on the influence of soil erosion intensity on the characteristics of hyperspectral reflectance, and such information would provide a new tool to improve quantitative understanding of soil erosion. In this study, 35 soil samples were collected from three regions with different erosion intensities in Changting County, a typical severely eroded county in the ferralic cambisol region of southern China, and classified into three groups according to different erosion controlling status. All the samples were scanned at wavelengths from 400 to 2,498 nm by an ASD Field Spec Portable Spectrometer, and the erosion intensity of each sample was calculated using the Revised Universal Soil Loss Equation. Multivariate stepwise linear regression was then employed to model the soil erosion intensity based on reflectance. The results suggested that the absorption peaks of each sample were in a similar wavelength range, while the absorption depth varied with different erosion status, and the reflectance of extremely eroded soil samples were the highest. During modelling of erosion intensity, the result was poor when all the samples were combined, but improved greatly at certain wavelength ranges when samples were classified into three groups based on different erosion controlling status. The extreme erosion group markedly outperformed the other two groups, in which the R ² values between the actual and predicted erosion intensity were 0.67, 0.85 and 0.80 for each spectral type. The results indicated that hyperspectral reflectance is a promising method for accurately monitoring erosion intensity.     

半干旱区内陆湖泊透明度高光谱估测模型研究——以松嫩平原查干湖为例

通过实测查干湖高光谱数据,建立透明度(Secchi Disk Depth,SDD)单波段估测模型、比值估测模型以及神经网络高光谱估测模型,并以确定性系数R2以及剩余残差RMSE为指标进行了验证.通过对单波段估测模型和比值估测模型进行比较发现,单波段模型估测结果与比值模型相差无几,而水体透明度经对数处理有利于模型精度提高,但是神经网络模型是三者中最优的.查干湖透明度高光谱定量估测模型的建立,有利于今后利用遥感影像,对查干湖水体透明度进行全面估测,对于研究和监测查干湖水体水质状况有重要意义.     

基于实测数据的不同雪粒径光谱分析

利用黑河流域上游冰沟流域样地的实测积雪光谱和实测雪粒径数据,对不同雪粒径的光谱曲线特征进行分析,找出位于1030 nm和1 250 nm附近对雪粒径较敏感的两个波长,定量地揭示了位于这两个波长附近处的光谱曲线特征与雪粒径的关系.1 030 nm和1 250 nm附近是雪反射光谱中两个较明显的吸收峰位置,但雪在这两处的反射率值依然较高.分别通过1 030 nm和1 250 nm附近吸收峰置差异、1 030 nm附近处的光谱吸收深度、光谱吸收面积等4种方法与雪粒径进行关系拟合.结果表明:光谱吸收面积法对雪粒径有很好的指示作用,与雪粒径的线性和指数曲线拟合效果最好.同时,1 030nm附近的波长受大气散射和衰减的影响很小,可将该方法直接运用到高光谱影像上.     

短波红外光谱技术在浅剥蚀斑岩铜矿区勘查中的应用——以西藏念村矿区为例

作为世界上最重要的一种矿床类型,斑岩铜矿一直是工业界勘查的首选.对此类矿床的勘查,在中-深剥蚀程度的矿区相对简单,而在浅剥蚀的矿区则变得较为困难,这是因为在浅剥蚀的矿区,矿床热液/矿化中心很难快速有效定位.近年来,在矿产勘查领域逐渐得到广泛应用的短波红外光谱技术,可通过特定蚀变矿物反射光谱特征参数系统变化的规律来厘定热液/矿化中心,在块状硫化物及浅成低温矿床中显示出良好的应用效果,这为浅剥蚀斑岩铜矿热液/矿化中心的快速、有效厘定提供了一种途径.为此,文章选择了位于冈底斯斑岩铜矿带东段、剥蚀较弱的念村(即夏玛日)矿区,拟通过矿区样品短波红外光谱的系统测量,寻找出蚀变矿物反射光谱特征参数系统变化的规律,进而约束矿床热液/矿化中心.本次研究在念村矿区共识别出7种蚀变矿物,按出现频率由多至少依次为伊利石、绿泥石、蛋白石、叶蜡石、高岭石、绿帘石及多硅白云母;而且,矿区外围以伊利石-绿泥石±绿帘石蚀变矿物组合为主,向内逐渐过渡为伊利石±蛋白石、伊利石-叶蜡石±高岭石组合.通过对伊利石反射光谱特征参数的计算发现,伊利石结晶度及Al-OH吸收峰位,这些通常被认为与伊利石形成温度有关的光谱学参数,在该矿区呈现出系统的变化规律:在矿区东北部,伊利石结晶度较大(＞1.6),Al-OH吸收峰位较小(＜2 203 nm),而该区域的外围,伊利石结晶度变小,Al-OH吸收峰位变大.这表明矿区东北部伊利石的形成温度更高,暗示该区域可能为矿床热液/矿化中心.因此,建议在本次研究所圈定的热液/矿化中心范围内,在适当开展物探工作的基础上,尽快布置勘查工程进行验证,以实现矿床的尽快查找和突破.     

Variations in composition and abundance of white mica in the hydrothermal alteration system at Hellyer,Tasmania, as revealed by infrared reflectance spectroscopy

Short-wave infrared (SWIR) spectral reflectance of hydrothermally altered volcanic rocks in the footwall of the Hellyer massive sulfide deposit was measured with a portable PIMA-II infrared spectrometer. The Al–OH band was used to derive information on the octahedral Al content and the abundance of white mica (sericite) in the hydrothermal alteration and mineralization system. The range of the Al–OH band wavelength from 2192 nm to 2222 nm corresponds to the number of octahedral Al (Al^vi) in white mica approximately from 3.9 to 3.0 (based on 4 octahedral cations per formula). This Al^vi range represents a significant compositional variation, covering most of the compositional region between muscovite (Al^vi = 4.0) and phengite (Al^vi = 3.0). Furthermore, the spectral reflectance data show that the compositional variation of white mica is spatially related to hydrothermal alteration zoning, such that phengitic white mica tends to occur in 1) main upflow fluid channel, 2) intensely altered volcanic rocks, and 3) Pb–Zn mineralization, whereas muscovitic white mica was formed preferentially distal to massive sulfide mineralization on the margin of the footwall alteration system. The results suggest that the Al–OH band wavelength, and therefore the octahedral Al content, of white mica can be used as vectors to mineralization to map the hydrothermal system at Hellyer.