基于光谱特征空间的苏必利尔湖型铁矿高光谱遥感蚀变信息提取方法

由于境外铁矿床位置偏远, 现场研究困难, 旨在探讨苏必利尔湖型铁矿的高光谱遥感蚀变信息提取方法, 为境外找矿提供依据.鉴于传统蚀变信息提取方法的局限性, 研究了在二维光谱特征空间中提取蚀变信息的方法.高光谱影像经主成分变换后, 包含较多地物信息的两个主成分的二维光谱特征空间体现了各向异性的特点, 不同地物的聚类常呈类似椭圆分布.在蚀变信息的聚类椭圆中圈定散点, 并应用波谱特征拟合, 将异常散点的平均光谱与美国地质调查局(United States Geological Survey, USGS)光谱库中的矿物光谱匹配, 确定蚀变矿物类型.以苏必利尔湖型铁矿——巴西Aguas Claras铁矿区为例, 提取了赤铁矿、绿泥石等蚀变矿物, 结果表明矿物的类型和分布与该区地质概况吻合.      

ASTER spectral analysis for alteration minerals associated with gold mineralization

This study presents classifications of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery based on spectral analysis of alteration minerals associated with gold mineralization in Abo Marawat area which is located in the Central Eastern Desert of Egypt. Spectral analysis of continuum removed reference spectra of alteration minerals alunite, kaolinite, sericite, and calcite from USGS and JPL spectral libraries show shifts in position, shape, and strength most probably related to changes in sample purity and particle size of analyzed samples. Spectral Information Divergence (SID) classification method proved successful for mapping sericite, calcite, and clay minerals. Spectral Angle Mapper (SAM) classification identified only sericite and calcite alteration minerals. The identified alteration zones are coincidence with the field sampling and geological map of the study area. The microscopic examination of samples collected from the quartz veins and hydrothermally altered wall-rocks from near surface and subsurface at Abu Marawat gold mine shows sericitization, argillaceous, and carbonatization alteration zones. Gold occurs as very fine inclusions in pyrite, chalcopyrite, and sphalerite and also found filling the fractures between chalcopyrite grains. This study concludes that ASTER image classifications using reference spectra are a stable and reproducible technique for mapping gold related hydrothermal alteration zones in areas with no dominant vegetation cover.     

Mediterranean forest mapping using hyper-spectral satellite imagery

Mediterranean forests are characterized by spatiotemporal heterogeneity that is associated with Mediterranean climate, floristic biodiversity and topographic variability. Satellite remote sensing can be an effective tool for characterizing and monitoring forest vegetation distribution within these fragmented Mediterranean landscapes. The heterogeneity of Mediterranean vegetation, however, often exceeds the resolution typical of most satellite sensors. Hyper-spectral remote sensing technology demonstrates the capacity for accurate vegetation identification. The objective of this research is to determine to what extent forest types can be discriminated using different image analysis techniques and spectral band combinations of Hyperion satellite imagery. This research mapped forest types using a pixel-based Spectral Angle Mapper (SAM), nearest neighbour and membership function classifiers of the object-oriented classification. Hyperion classification was done after reducing Hyperion data using nine selected band combinations. Results indicate that the selection of band combination while reducing the Hyperion dataset improves classification results for both the overall and the individual forest type accuracy, in particular for the selected optimum Hyperion band combination. One shortcoming is that the performance of the best selected band combination was superior in terms of both overall and individual forest type accuracy when applying the membership classifier of the object-oriented method compared to SAM and nearest neighbour classifiers. However, all techniques seemed to suffer from a number of problems, such as spectral similarity among forest types, overall low energy response of the Hyperion sensor, Hyperion medium spatial resolution and spatiotemporal and spectral heterogeneity of the Mediterranean ecosystem at multiple scales.     

植被覆盖区卫星高光谱遥感岩性分类

植被高覆盖区岩石和土壤在遥感图像上表现为弱信息、小目标,如何利用卫星高光谱遥感提取岩性弱信息是目前遥感地质应用中的最大挑战之一。以黑龙江呼玛地区为例,选择美国EO-1卫星Hyperion高光谱数据。由于植被与下伏岩石-土壤的光谱混合,分别计算研究区含土壤因子和不含土壤因子的植被指数,并对两类不同的植被指数进行主成分分析,以此分离植被和岩石-土壤组分。在含土壤因子植被指数主成分分析的二维组分散点图上,明显区分出背景植被与异常岩石-土壤组分,证实了植被与岩石-土壤组分经主成分分析分离的效果。同时在不添加土壤因子植被指数的分析中,明显区分出植被覆盖信息。通过对实验区典型岩石进行野外光谱测试,然后对光谱进行连续统去除处理,将其作为参考光谱,与分离后的岩石-土壤光谱进行光谱特征拟合（SFF）,从而成功地识别出研究区内不同岩石类型,特别是玄武岩、流纹岩、砂砾岩、安山质凝灰岩、大理岩和石英片岩识别效果较好。根据研究区内不同岩石地层单元内岩石组合特征,通过分离后的组分合成图像,成功地实现了岩性分类。与已知地质图叠加,证实通过卫星高光谱数据提取的不同岩石类型颜色边界与地质图岩性界线吻合较好。结果表明：通过植被与岩石-土壤光谱组分分离,结合高光谱遥感的光谱特征拟合,能够识别不同的岩石类型,实现植被覆盖区岩性分类。     

Hyperion高光谱遥感在青海东昆仑东大滩地区找矿中的应用

利用ENVI软件,对青海东昆仑东大滩地区Hyperion高光谱数据进行处理后,运用光谱角填图法、波谱特征拟合法及匹配滤波法,对高光谱数据进行了矿物蚀变信息的提取,获得了东大滩地区矿物蚀变图像。在磨石沟二长花岗岩、花岗闪长岩岩体外围的南东侧,存在着硅酸盐、碳酸盐、三价铁等矿物蚀变。野外对蚀变异常地段进行验证,野外观察的矿物蚀变异常与遥感图像显示的蚀变异常区域基本吻合;结合区域地质背景与成矿条件,进行了区内成矿预测与优选靶区圈定,并发现了东大滩铜矿化点,说明高光谱遥感能为找矿提供准确且可靠的信息。     

植被覆盖区羟基和碳酸盐矿物光谱吸收深度校正模型

为增强植被覆盖区羟基和碳酸盐矿物的吸收特征, 提高矿物信息提取精度.通过模拟单像元内新鲜植物、干枯植物、羟基和碳酸盐矿物的混合光谱, 发现在一定波段范围内4种端元的特征波段处吸收深度呈显著线性关系, 并建立了羟基和碳酸盐矿物的植物校正吸收深度(vegetation corrected continuum depths, VCCD)模型.将模型应用于黑龙江呼玛的Hyperion影像, 提取了高岭石和方解石矿物信息.在去除河床、道路等干扰信息后, 经野外实地验证和室内岩石鉴定, 矿物信息提取结果较好.      

德兴铜矿矿山污染高光谱遥感直接识别研究

利用高光谱图谱结合特征开展矿山污染直接识别研究.首先详细分析了德兴铜矿矿山污染(废矿、废水以及植被) 地物的光谱特征, 总结出可利用于直接识别和提取这些污染物的特征光谱, 从而利用矿区航天Hyperion高光谱数据并以矿物识别谱系技术为主有效地识别出矿区的污染类型及其分布.对于以黄铁矿等含铁矿物为主的围岩或贫矿矿石的氧化污染利用70 0nm、10 0 0nm以及2 2 0 0nm附近的特征吸收分别识别出含Fe3 + 矿物及其Fe2 + 和Fe3 + 混合矿物, 并进一步根据光谱特征识别出赤铁矿和针铁矿; 根据矿区水体在6 0 0nm附近吸收特征的差异相对区分出酸性水、碱性水和中性水; 根据植被在6 85nm附近的最大吸收深度相对地划分植被污染程度.最后建议建立矿山污染地物光谱数据库.该研究为利用高光谱的技术优势快速且有效地直接识别与提取出污染源的种类、类型并分析其潜在的污染趋势提供了新的思路, 为矿山污染监测、治理规划和复垦提供了新技术和知识支撑.      

Hyperion高光谱遥感岩性识别填图

Hyperion高光谱数据在蚀变矿物填图方面已凸显其优越性,而在岩性识别方面大多仍在探讨中.通过应用Hyperion数据结合野外光谱采集,在研究区进行了岩性填图的试验研究.同时,叙述了野外采集光谱数据的过程,建立了野外实测光谱数据库,利用野外实测岩石光谱作为端元光谱进行SAM(Spectral Angle Match)光谱角岩性填图.这对于地质环境复杂地区的岩性填图工作具有一定的应用价值.     

Copper Ore Identification using Spectral Similarity Measurement from Hyperion Image,Mapping of Porphyry Copper Mineralized Zone

This work illustrates the effectiveness of hyperspectal image spectroscopy and lab spectroscopy in identification techniques of minerals in alteration zone of ore body. The adopted procedure involves testing of Hyperion image spectra, their processing for noise, spectral matching and spectral similarity measurement with selected library spectra. Average weighted spectral similarity; visual and statistical matching techniques were used to select end-members from image spectra. Minimum noise fraction and pixel purity index technique were used to retrieve end-member spectra from hyperion image. Hyperspectral image like hyperion has the capability to deliver laboratory standard spectroscopic result. This paper illustrates the capability of hyperion image spectra in copper ore identification and mapping of chalcopyrite outcrop. A systematic approach has been made in this paper. This approach describes how image end member spectra and laboratory spectra can be co-related to fetch accurate spectral form of chalcopyrite ores. Thus, statistical and graphical comparison has been carried out between image derived end member spectra and laboratory spectra of chalcopyrite for better accuracy. The visual measurements is satisfactory, R = 0.973 for fine and 0.976 for medium grained chalcopyrite ore. Excellent statistical significance levels (90–97%) are found while comparing these spectra. There are many success stories of sub-pixel and N-dimensional feature space methods to separate the hydrothermal alteration zones from iron oxide mixed ore bodies. Thus, unmixing methods are very useful for mapping of most dominating mineral parts of a pixel from hyperspectral images which have coarse spatial resolution. Finally, mapping of mineralized zone has been achieved through sub-pixel based classifiers like spectral angle mapper (SAM), constrained energy minimization (CEM) and adaptive coherence estimator (ACE) techniques.     

Mineralogy, geochemistry, and origin of hydrothermal manganese veins at Wadi Maliek, Southern Eastern Desert, Egypt

The present work deals with the geology, mineralogy, geochemistry, and origin of the metagabbroic-hosted manganese deposits at Wadi Maliek in the southern Eastern Desert of Egypt. The manganese veins are found in the shear zones and channel ways of the fault planes within the metagabbroic rocks pointing to those hydrothermal solutions carrying manganese and iron load penetrating along these fractures. These faults are striking N 80° E?CS 80° W with dipping 65°. These veins vary in thickness from 15?cm up to 125?cm wide; each vein may show difference in thickness from bottom to top. Microscopic examinations, X-ray diffraction, infrared spectral, differential thermal (DTA), thermogravimetric (TGA), and ESEM-EDAX analyses revealed that the manganese minerals consist mainly of pyrolusite, psilomelane, and ramsdellite. Goethite and hematite are the common iron minerals. Petrographically, the manganese deposits can be classified into three ore types based on the predominance of manganese and iron minerals: manganese, manganese?Ciron, and iron ore types. The geochemistry of Maliek deposits indicated that the total averages of some major oxides in manganese, manganese?Ciron, and iron ore types are respectively as follows: SiO₂ (15.64%, 11.52%, and 20.58%), MnO (39.9%, 17.81%, and 0.77%), FeO* (7.13%, 33.31%, and 37.08%), CaO (5.89%, 5.82%, and 5.32%), and Na₂O (1.04%, 1.61%, and 1.53%). With regard to trace elements, the Maliek manganese deposits are rich in Zn, Ba, Pb, Sr, and V. Based on the geological, mineralogical, and geochemical results, the studied manganese deposits are considered to be precipitated from hydrothermal solution.     

ASD field hyperspectral measurements for discrimination of the ferruginous rocks and the iron ore types at El Gedida-Ghorabi area,Bahariya Oasis,Western Desert,Egypt

The ironstone succession at El Gedida-Ghorabi-Naser area of El Bahariya depression is subdivided into lagoonal manganiferous mud and fossiliferous ironstone consisting mainly of hematite and goethite-hydrogoethite. The application of the ASD field spectroradiometer measurements (spectral range) in the ASTER data led to the interpretation of the presence of ferruginous units as quartzitic sandstone, gluconitic sandy clay, and pink marly limestone. The existing iron ore minerals in the iron ore localities were also classified into high Mn hematite, low Mn hematite, goethite, hydrogoethite as well as low- and high-grade Hematite and Barite. Quartz, feldspars, rutile, and clay minerals (e.g., kaolinite and illite) are mainly associated with the iron ore. Accessory minerals of manganese, e.g., psilomelane and pyrolusite, were also present. The Barite mineral is recorded as a common mineral association with the iron ore deposits at El Gedida and Ghorabi localities. The stratigraphical units investigated in the study area include the oldest gravely clayey sandstones of the Bahariya Formation overlain by the fossiliferous and oolitic limestones of the El-Hamra, Qazzun, and Naqb Formations. Quartztic sandstones and clayey sandstones of the Radwan Formation and youngest Quaternary sediments of sandy-clayey materials were often found as intermittent cover and overburden in unconformity surfaces over the iron ore bands.     

基于Hyperion高光谱数据和随机森林方法的岩性分类与分析

探索利用高光谱数据的岩性填图新方法是遥感地质应用领域的重要需求之一。本文运用随机森林方法和EO-1Hyperion高光谱数据,对新疆塔里木西北部柯坪地区的局部区域进行岩性分类,并对相关问题进行分析。分别利用光谱特征以及加入光谱一阶导数特征进行岩性分类,并对不同特征对岩性分类的重要性进行分析,同时与现有的基于光谱角制图方法(SAM)进行比较。结果表明,与SAM方法相比,随机森林方法得到了更高精度的岩性分类结果,是一种有效可行的岩性分类方法。根据特征重要性的排序,蓝绿光波段、短波红外波段以及相应的一阶导数特征对研究区Hyperion数据的沉积岩岩性分类贡献更大。     

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.     

Identification and mapping of clay minerals in the region of Djebel Meni (Northwestern Algeria) using hyperspectral imaging,EO-1 Hyperion sensor

Applied in Djebel Meni (Northwestern of Algeria), this research highlights the results obtained from the supervised classification using the Spectral Angle Mapper (SAM) algorithm, through introducing the spectral signatures of illite, kaolinite, and montmorillonite, via Jet Propulsion Laboratory (JPL) spectral library. These results were compared to the ones of the SAM classification, which use spectral signatures obtained by the Sequential Maximum Angle Convex Cone (SMACC) endmembers extraction algorithm. This implies the ability to detect and identify any object present on the Earth’s surface, whether its nature is mineral, vegetal, or human made, from hyperspectral imaging. By extracting the spectral signatures with the SMACC algorithm and matching them to the current signatures of JPL spectral library, comparing spectral signatures with another is not an easy task. Indeed, for a better comparison and a more appropriate interpretation in the use of the SAM classification, the results obtained were very relatively convincing because, regarding very strong similarities. It appears also that the signatures extracted with SMACC occupy the same areas as those of the JPL spectral library. This method of detection and identification of any present object on the Earth’s surface is rather conclusive.     

Goethite Morphology and Composition in Banded Iron Formation, Orissa, India

Iron ore deposits are generally described in terms of size, grade and chemical composition rather than the mineralogical and microstructural characteristic of different ore types. It is essential, however, to know the morphology, microstructure and chemical composition of individual minerals for optimum mineral processing. Goethite is reported to occur as a ubiquitous phase in many iron ore types and is particularly abundant in the Precambrian banded iron ore formation of north Orissa, India. Goethite from the Bonai–Keonjhar Belt in Orissa has been examined in terms of its morphology and microstructure in relation to chemical composition. Electron microscopy indicated several goethite morphotypes including botryoidal, nodular, spheroidal, platy, stalactitic and flaky. These different morphotypes display intergranular, intragranular, wedge, reniform, comb, prismatic, cavity-line and bead microstructures. In situ analysis using electron probe microanalyzer indicated a wide compositional variation among the different morphotypes and microstructures. Goethite replacing hematite is generally devoid of deleterious elements while re-precipitated goethite generally contains adsorbed alumina, silica and/or phosphorus. Nodular goethite commonly has a high phosphorus level while botryoidal, spheroidal and platy goethite often contains increased combined alumina and silica. Goethite having a reniform, wedge, intergranular or intragranular microstructure is highly water bearing and cryptocrystalline in nature. During dehydration, bead, comb, cavity-lined or prismatic goethite develop, which are more crystalline and which have a higher iron concentration. Goethite with a wedge, prismatic or bead-type microstructure has a higher adsorption of silica (2–4%), while goethite having an intergranular, bead or prismatic microstructure invariably contains appreciable phosphorus, generally at levels deleterious to processing.     

The Mechanisms of Enlargement and Hydrogeological Characteristics of Nanka Gully,Southeast Nigeria

Jharkhand is well known for the largest iron deposits in India. Noamundi is the main deposit, which is associated with shale, keolinite. The rock succession exposed in the southern Singbhum and Keonjhar and lying unconformably over the older metamorphics are known as Iron Ore Series (Ravindrakumar, 1986). This paper relates the assessment of grades of iron ore of the area. The study involves with pre-processing, FLAASH (Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes) Atmospheric correction algorithms of EO-1 Hyperion data and evaluating the spectral characteristic by using ENVI 4.7 software package. The position of peak reflectance and absorption trough, continuums removal and absorption band depth are considered for assessment the spectral characters. The strong absorption observed is between the 860 to 900nm wavelength region and peak reflectance is observed in the 750 to 780nm wavelength region of the image spectra. The position of the NIR absorption trough shift to the direction of the longer wavelengths is due to decrease of iron content. Higher values of band depth indicate a better possibility of the iron occurrence. As a result, this spectral study enables the possibility to differentiate the grades of iron ores from hyperspectral satellite images.     

Hyperspectral satellite data analysis for pure pixels extraction and evaluation of advanced classifier algorithms for LULC classification

The study was carried out for Indian capital city Delhi using Hyperion sensor onboard EO-1 satellite of NASA. After MODTRAN-4 based atmospheric correction, MNF, PPI and n-D visualizer were applied and endmembers of 11 LCLU classes were derived which were employed in classification of LULC. To incur better classification accuracy, a comparative study was also carried out to evaluate the potential of three classifier algorithms namely Random Forest (RF), Support Vector Machines (SVM) and Spectral Angle Mapper (SAM). The results of this study reemphasize the utility of satellite borne hyperspectral data to extract endmembers and also to delineate the potential of random forest as expert classifier to assess land cover with higher classification accuracy that outperformed the SVM by 19% and SAM by 27% in overall accuracy. This research work contributes positively to the issue of land cover classification through exploration of hyperspectral endmembers. The comparison of classification algorithms’ performance is valuable for decision makers to choose better classifier for more accurate information extraction.     

Enhancement of hydrothermal alteration zones using the spectral feature fitting method in Rabor area, Kerman, Iran

Rabor exploration area is in southeast of Kerman province, south of Urumieh-Dokhtar volcanic belt. Since there are many evidences of porphyry copper mineralization in this belt, prospecting and exploration of the intact and undiscovered places, especially the southern part of this belt, seems necessary. In this paper, use has been made of the “spectral feature fitting” (SFF) method to process ASTER satellite data (in Rabor exploratory area as a case study) for the identification and enhancement of hydrothermal alteration zones related to probable porphyry copper mineralization. The method is based on the comparison of absorption features in the image and the reference spectra. The distribution map of the indicator clay minerals, such as kaolinite, muscovite, illite, montmorillonite, alunite, pyrophyllite, dickite, chlorite, and epidote in Rabor exploratory area has been prepared with the help of this method. Identification and enhancement of alteration zones and overlaying Pay-Negin ore index on every individual zone reveal the capability and high efficiency of the SFF method in processing ASTER satellite data and preparing the distribution map of alteration minerals. Field and laboratory studies have shown that main alterations in this area are phyllic and argillic. These studies confirm the results obtained from remote sensing in the area.     

植被覆盖区高光谱蚀变矿物信息提取

在植被覆盖严重地区,基于综合光谱信息模型,开展了高光谱遥感典型蚀变矿物信息提取研究.以河北省承德市大营子地区为例,利用Hyperion数据,在植被覆盖度大于70%的地区,根据蚀变矿物与背景地物波谱特征的差异,提取了该区绿泥石、斜绿泥石、方解石和白云石蚀变矿物分布信息,与已知地质矿产资料及野外检查结果一致.最后依据蚀变矿...     

A Comparative Study of Landsat‐7 and Landsat‐8 Data Using Image Processing Methods for Hydrothermal Alteration Mapping

Comparing spaceborne satellite images of Landsat‐8 Operational Land Imager (OLI) and Landsat‐7 Enhanced Thematic Mapper plus (ETM+) was undertaken to investigate the relative accuracy of mapping hydrothermal alteration minerals. The study investigated the northern part of Rabor, which contains copper mineralization occurrences, and is located in the Kerman Cenozoic magmatic assemblage (KCMA), Iran. Image processing methods of band ratio, principal component analysis (PCA), and spectral angle mapper (SAM) were used to map the distribution of hydrothermally altered rocks associated with the porphyry copper mineralization. The band ratio combination of both sensors for mapping altered areas showed similar outcomes. PCA exposed variations in the spatial distribution of hydroxyl‐bearing minerals. The representation of hydrothermal areas using OLI data was more satisfactory than when using ETM+ data. SAM analysis found similar results for mapping hydroxyl‐bearing zones. Verification of the results came through ground investigation and laboratory studies. Rock samples (n = 56) were collected to validate results using thin sections, X‐ray diffraction (XRD) and spectral analyses. Field observations and laboratory analysis revealed that phyllic and propylitic alterations dominate the alteration zones in the study area. Argillic and iron oxides/hydroxides alterations were observed to a lesser degree. The results indicate that alteration maps prepared by OLI data using PCA for visual interpretation are more suitable than those of ETM+ due to a higher radiometric resolution and lower interference between vegetation and altered areas. As the spectral bandwidth of ETM+ band 7 covers absorption feature of propylitic alteration, better mapping of propylitic alterations is achieved using ETM+ data.