影像空间分辨率对蚀变信息提取结果的影响研究

脉状蚀变分布广泛且蚀变规模一般较小，遥感影像空间分辨率对此类蚀变提取影响严重。为了评估不同空间分辨率数据对脉状矿化蚀变信息的提取能力，以甘肃北山金滩子地区为例，应用航空高光谱CASI/SASI数据，将像元重采样至5、10、15、20和30 m共5种空间分辨率模式；以JPL光谱库中白云母矿物光谱曲线为参考，利用光谱匹配滤波法提取区内白云母化蚀变。不同规模蚀变带在5种分辨率模式下像元光谱表明：面状蚀变由于面积较大，空间分辨率变化对像元光谱吸收特征影响较小；脉状蚀变带特别是较窄脉状蚀变带随着空间分辨率的降低，混合像元影响越来越强，像元光谱的吸收特征越来越浅，30 m空间分辨率时吸收特征最弱。5种空间分辨率影像的白云母矿物提取结果表明较窄蚀变带(宽约1~5 m)在5~15 m空间分辨率图像中均线状特征明显，在20 m分辨率数据结果中仅断续出现，在30 m空间分辨率结果中仅个别像元被突出。     

多维空间角度方法提取植被覆盖区蚀变信息

基于光谱角制图法，提出运用多维空间角度方法来提取植被覆盖较好区域的遥感图像蚀变信息。采用目视解译方法得到的样本向量代替从波谱库中得到的端元组分矢量来计算多维向量间的空间角，并且加入合适的约束条件，来改进多维空间角度方法。给出了植被覆盖区蚀变信息提取的实施方法与步骤。最后运用改进的多维空间角度方法提取实际区域的蚀变信息，并将它与用比值法和主成分分析法得到的结果作比较。表明改进的多维空间角度方法提取蚀变信息的效果比较理想，与该地区的地质图件更为一致，从而证实了该方法的有效性。     

影像空间分辨率对蚀变信息提取结果的影响研究

脉状蚀变分布广泛且蚀变规模一般较小,遥感影像空间分辨率对此类蚀变提取影响严重。为了评估不同空间分辨率数据对脉状矿化蚀变信息的提取能力,以甘肃北山金滩子地区为例,应用航空高光谱CASI/SASI数据,将像元重采样至5、10、15、20和30 m共5种空间分辨率模式;以JPL光谱库中白云母矿物光谱曲线为参考,利用光谱匹配滤波法提取区内白云母化蚀变。不同规模蚀变带在5种分辨率模式下像元光谱表明：面状蚀变由于面积较大,空间分辨率变化对像元光谱吸收特征影响较小;脉状蚀变带特别是较窄脉状蚀变带随着空间分辨率的降低,混合像元影响越来越强,像元光谱的吸收特征越来越浅,30 m空间分辨率时吸收特征最弱。5种空间分辨率影像的白云母矿物提取结果表明较窄蚀变带(宽约1~5 m)在5~15 m空间分辨率图像中均线状特征明显,在20 m分辨率数据结果中仅断续出现,在30 m空间分辨率结果中仅个别像元被突出。     

基于SAM与SVM的高光谱遥感蚀变信息提取

高光谱遥感技术的发展,提高了遥感技术的定量化水平,要求人们从光谱维去理解地物在空间维的变换。提出了一种光谱角匹配技术（Spectral Angle Mapper,SAM）与支持向量机（Support Vector Machine,SVM）相结合的高光谱遥感蚀变信息提取模型,在光谱维提取地表的蚀变信息。鉴于SAM算法仅考虑波谱矢量方向,忽略辐射亮度大小的缺点,利用SVM算法对SAM的提取结果进行二次分类,利用网格搜索法并结合分类精度评估进行参数寻优。通过AVIRIS高光谱数据实验证明,提取的蚀变信息分类精度为78.172 6%,Kappa系数为0.712 5。该模型计算方便,对于解决光谱维的地物分类及相似矿物的蚀变信息提取具有一定的实际意义。     

基于岩矿蚀变组分特征光谱定量反演遥感蚀变信息研究

通过研究区实测蚀变岩矿样品光谱,在ASTER数据波段上重建其光谱曲线,分析岩矿蚀变组分丰度与其特征光谱参数的相关性,优选特征光谱参数与蚀变组分含量进行多元统计分析,推导出岩矿蚀变组分与AS-TER遥感数据各波段之间的回归函数,建立羟基蚀变遥感异常反演模型。这一方法在新?老山口地区应用,分别提取出了Al-OH、Mg-OH矿物遥感蚀变异常。与传统的比值、主成分分析等方法提取的遥感蚀变异常相比,本方法充分利用了各蚀变组分的光谱特征信息,提取的蚀变异常客观可靠,更符合区域矿产实际。     

高寒山区矿化蚀变信息提取的应用研究

从遥感影像中准确地提取矿化蚀变信息有着重要的理论和现实意义。本文中,作者利用ETM+多光谱数据,针对新疆西天山地区特殊的高寒山区特点,提出了一种改进的光谱角分类法——定量光谱角分类法来进行矿化蚀变信息提取。通过试验研究表明,该方法能够有效地提取矿化蚀变信息,具有一定的理论参考价值。     

组合分析蚀变信息提取方法研究

目前主成分分析法、比值法、光谱角制图法等已广泛应用于遥感矿化蚀变信息提取中,且取得了很好的效果。根据研究区遥感数据特点,采用比值与主成分组合分析的方法,结合FLAASH大气校正、中值滤波以及彩色密度分割等图像处理方法,对新疆且末地区ASTER数据进行蚀变信息提取。经USGS标准矿物波谱库中典型矿物光谱的验证,组合分析方法能够去除数据冗余和噪声,有利于各类蚀变信息的提取。     

基于ETM数据的蚀变遥感异常信息提取及成矿区预测研究-以甘肃党河南山地区为例

遥感成矿探测技术关键在于成矿构造及蚀变矿物信息的提取。以甘肃酒泉党河-南山地区为研究区,基于ETM数据和ASTER遥感数据,利用主成分变换、掩膜分析、阈值分割等方法,从Landsat\|7 ETM数据中提取矿化蚀变信息并预测可能成矿的区域。该方法准确、有效地消除了云、雪等干扰信息,利用该方法获得的矿化蚀变信息与已知矿点有很好的一致性,因此用该方法提取蚀变信息是可行的。     

分形方法在遥感蚀变信息提取中的应用研究

分形方法已经成为提高勘查地球化学、地球物理信息的重要途径之一,但该方法在遥感数据处理领域的应用研究较少。以河南卢氏木桐钼铁多金属矿区为实验区,ETM+遥感影像为数据源,运用MPH与波段比值、滤波等方法组合提取该实验区的蚀变信息。采用分形理论的求和法像元亮度-面积模式,对所提取出来的铁染蚀变进行定量分析,并与传统阈值选取方法进行了对比研究。结果表明蚀变作为一种地质记录,其空间展布不仅具有分形特征,而且具有多重分形的特征,在此基础上,对实验区遥感蚀变异常进行分级,弥补了传统的门限化方法和利用灰度直方图目视确定突变点方法的不足,取得了较好效果。     

矿化蚀变信息的遥感提取方法综述

金属矿床通常伴随近矿围岩蚀变，因此矿化蚀变信息的提取对于找矿具有十分重要的意义。本文介绍了国内外利用遥感数据提取矿化蚀变信息的研究历史、现状及几种常用的方法，如比值变换，主成分分析，光谱角填图，对应分析法．Gramschmidt投影方法，混合像元分解法和MPH技术，详细介绍了这些方法的核心技术及成功实例。最后将这些方法做了对比分析，指出了每种方法的针对性及优缺点。     

秘鲁中南部奥马斯地区铜多金属遥感找矿预测研究

利用ASTER多光谱卫星数据,根据研究区内蚀变矿物的波谱特性,采用特征波段组合的主成分分析方法进行蚀变矿物组合信息提取,分别提取了绢云母、高岭石、蒙脱石、伊利石和明矾石等Al-OH类蚀变矿物组合信息,以及绿泥石、绿帘石和碳酸盐化(方解石和白云石)等青磐岩化类蚀变矿物组合信息。同时采用人机交互解译技术在研究区开展了遥感地质解译,结合区域成矿地质特征,综合分析了研究区控矿线性构造、环形构造、赋矿岩层和蚀变矿物组合等遥感示矿信息,并基于遥感示矿信息进行了综合找矿预测,圈定出遥感找矿有利区,经地面水系沉积物化探填图和高分辨卫星影像佐证,研究表明圈定的遥感找矿有利区为研究区开展地面矿产勘查工作提供重要的参考依据。     

Investigation of heavy-mineral deposits using multispectral satellite data

Mineral deposit mapping is essential for sustainable and eco-friendly exploitation of natural resources. The south Tamil Nadu coast of India is rich in minerals. Currently the beach sands are extracted for export entirely in raw form without any value addition. Due to unsustainable sand mining, there are negative environment impacts, which lead to various coastal hazards such as erosion, salinization and sea-water intrusion. In order to initiate the focus on mapping of mineral deposits along this area, standardized hyperspectral analysis has been carried out using Landsat satellite data and Environment for Visualising Images (ENVI) software. The selected endmembers are identified by comparing the spectral signatures with predefined spectral plots from the United States Geological Survey (USGS) spectral library. Finally the endmembers are mapped with ENVI's spectral angle mapper (SAM). The minerals which show significant variation in reflectance at different spectral bands can be effectively mapped by using multispectral data. Ground verifications performed to assess the accuracy of classification were mostly in agreement with the obtained results. This study has opened up new areas for inland heavy mineral exploitation and leads to eco-friendly exploitation of natural resources along the study area. It also illustrates the high potential of multispectral satellite data for exploration and mapping of mineral resources.     

Utilization of Hyperion data over Dongargarh,India, for mapping altered/weathered and clay minerals along with field spectral measurements

Hyperion data acquired over Dongargarh area, Chattisgarh (India), in December 2006 have been analysed to identify dominant mineral types present in the area, with special emphasis on mapping the altered/weathered and clay minerals present in the rocks and soils. Various advanced spectral processes such as reflectance calibration of the Hyperion data, minimum noise fraction transformation, spectral feature fitting (SFF) and spectral angle mapper (SAM) have been used for comparison/mapping in conjunction with spectra of rocks and soils that have been collected in the field using Analytical Spectral Devices's FieldSpec instrument. In this study, 40 shortwave infrared channels ranging from 2.0 to 2.4 μm were analysed mainly to identify and map the major altered/weathered and clay minerals by studying the absorption bands around the 2.2 and 2.3 μm wavelength regions. The absorption characteristics were the results of O–H stretching in the lattices of various hydrous minerals, in particular, clay minerals, constituting altered/weathered rocks and soils. SAM and SFF techniques implemented in Spectral Analyst were applied to identify the minerals present in the scene. A score of 0–1 was generated for both SAM and SFF, where a value of 1 indicated a perfect match showing the exact mineral type. Endmember spectra were matched with those of the minerals as available in the United States Geological Survey Spectral Library. Four minerals, oligoclase, rectorite, kaolinite and desert varnish, have been identified in the studied area. The SAM classifier was then applied to produce a mineral map over a subset of the Hyperion scene. The dominant lithology of the area included Dongargarh granite, Bijli rhyolite and Pitepani volcanics of Palaeo-Proterozoic age. Feldspar is one of the most dominant mineral constituents of all the above-mentioned rocks, which is highly susceptible to chemical weathering and produces various types of clay minerals. Oligoclase (a feldspar) was found in these areas where mostly rock outcrops were encountered. Kaolinite was also found mainly near exposed rocks, as it was formed due to the weathering of feldspar. Rectorite is the other clay mineral type that is observed mostly in the southern part of the studied area, where Bijli rhyolite dominates the lithology. However, the most predominant mineral type coating observed in this study is desert varnish, which is nothing but an assemblage of very fine clay minerals and forms a thin veneer on rock/soil surfaces, rendering a dark appearance to the latter. Thus, from this study, it could be inferred that Hyperion data can be well utilized to identify and map altered/weathered and clay minerals based on the study of the shape, size and position of spectral absorption features, which were otherwise absent in the signatures of the broadband sensors.     

基于图像模拟的蚀变矿物信息提取技术评价

针对不同混合背景下蚀变矿物信息提取技术的响应程度这一问题,基于图像模拟,采用比值法(RM)、主成分分析法(PCA)和光谱角匹配法(SAM)3种蚀变矿物信息提取技术针对两种蚀变矿物(羟基、铁染)在模拟野外地物混合背景的情形下进行提取实验,并进行响应程度的定量统计和对比分析。结果表明:无论是纵向(不同算法之间)还是横向(同种算法针对不同种矿物蚀变信息)的算法响应程度均存在差异性,通过寻找响应程度的大致相同区间,可以在彼此间建立联系的纽带。不同的响应程度对应的丰度值能够反映不同算法针对两种蚀变矿物信息所能提取出来的大致混合背景。实验结果对于在不同混合背景下的合理选取算法及算法提取效果的对比评价等方面都具有实际参考价值。     

Spectral enhancement of selected pixels in Thematic Mapper images of the Guanajuato district (Mexico) to identify hydrothermally altered rocks

The use of satellite Thematic Mapper (TM) images in mineral exploration has been very successful in pointing out the presence of key minerals. Here we present the results of the spectral enhancement of a TM image to identify oxides and hydroxyl-bearing minerals in the Guanajuato district, using the two methods that yielded the best results in this area: band subtraction and principal component analysis on an image that included only selected pixels and excluded areas that did not present any interest for mineral exploration. Different types of vegetation cover the study area: crops, bushes and forest. Previous application of conventional methods was used to identify areas where the spectral signatures suggested the presence of hydrothermal alteration, and further detailed spectral enhancement in selected pixels allowed the identification of alteration minerals in areas covered with different vegetation types that do not have a similar spectral response. A field check performed using a PIMA (Portable Infrared Mineral Analyser) spectrometer yielded a good correlation of the marked areas with the presence of hydrothermally altered rock. New areas with argillic alteration were discovered in the Sierra de Guanajuato and the San Anton areas. Also, the main structures were determined by applying several filters to the first principal component. The occurrence of hydrothermal alteration and the presence of main faults were used to define areas favourable for further detailed exploration programmes.     

Identification of spectrally similar materials using the USGS Tetracorder algorithm: the calcite-epidote-chlorite problem

A scheme to discriminate and identify materials having overlapping spectral absorption features has been developed and tested based on the U.S. Geological Survey (USGS) Tetracorder system. The scheme has been applied to remotely sensed imaging spectroscopy data acquired by the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument. This approach was used to identify the minerals calcite, epidote, and chlorite in the upper Animas River watershed, Colorado. The study was motivated by the need to characterize the distribution of calcite in the watershed and assess its acid-neutralizing potential with regard to acidic mine drainage. Identification of these three minerals is difficult because their diagnostic spectral features are all centered at 2.3 μm, and have similar shapes and widths. Previous studies overestimated calcite abundance as a result of these spectral overlaps. The use of a reference library containing synthetic mixtures of the three minerals in varying proportions was found to simplify the task of identifying these minerals when used in conjunction with a rule-based expert system. Some inaccuracies in the mineral distribution maps remain, however, due to the influence of a fourth spectral component, sericite, which exhibits spectral absorption features at 2.2 and 2.4 μm that overlap the 2.3-μm absorption features of the other three minerals. Whereas the endmember minerals calcite, epidote, chlorite, and sericite can be identified by the method presented here, discrepancies occur in areas where all four occur together as intimate mixtures. It is expected that future work will be able to reduce these discrepancies by including reference mixtures containing sericite.     

基于GMM和ANN混合模型的语音转换方法

为了克服利用高斯混合模型(GMM)进行语音转换的过程中出现的过平滑现象,考虑到GMM模型参数的均值能够表征转换特征的频谱包络形状,本文提出一种基于GMM与ANN混合模型的语音转换,利用ANN对GMM模型参数的均值进行转换;为了获取连续的转换频谱,采用静态和动态频谱特征相结合来逼近转换频谱序列;鉴于基频对语音转换的重要性,在频谱转换的基础上,对基频也进行了分析和转换。最后,通过主观和客观实验对提出的混合模型的语音转换方法的性能进行测试,实验结果表明,与传统的基于GMM模型的语音转换方法相比,本文提出的方法能够获得更好的转换语音。     

基于主成分分析的植被掩模与模式滤波方法在中等植被区蚀变信息提取中的应用

植被干扰的消除对于应用ＴＭ图象进行蚀变信息提取是非常重要的。本文从矿物、岩石和植被在ＴＭ波段内的波谱响应分析入手，选择了ＴＭ５和ＴＭ１，ＴＭ５和ＴＭ７，ＴＭ４和ＴＭ３这三个组合分别来增强含铁矿物（主要是铁氧化物）、含羟基矿物和碳酸盐矿物及植被信息。通过对比值、比值合成以及主成分分析等方法的比较，提出了一种适合于中等植被覆盖区蚀变信息提取的新方法，即基于主成分分析的植被掩模和模式滤波相结合的方法。此方法在试验区进行蚀变信息提取中取得良好效果，它不仅识别出了与地表金矿化区一致的蚀变矿物富集区，而且对于土石矿区的一些矿脉也有较好反映。     

Design of a feature-tuned ANN model based on bulk rock-derived mineral spectra for endmember classification of a hyperspectral image from an iron ore deposit

In this article, a new feature-tuned artificial neural network (ANN) model has been developed for endmember classification of a hyperspectral image. This model is developed on the basis of using only the essential absorption bands of mineral spectra as opposed to using all the spectral bands of the hyperspectral image. This approach has the added advantages of reducing the dimensionality of input features to the ANN as well as inhibiting the influences of noisy bands for classification of endmembers. The proposed ANN model is trained using input features extracted from laboratory spectra of in situ bulk ore materials collected from an existing iron ore deposit. The input features are basically the constituent absorption bands of mineral spectra where each absorption band is mathematically characterized by the centre, width, and strength parameters of a Gaussian curve. For extracting absorption bands from a mineral spectrum, a modified Gaussian model has been used. The application of this model also necessitates the design of a special template for the input layer ANN model. After training the model, its generalization property is assessed through a testing data set. The model has achieved nearly 97% of classification accuracy in a training set, and 71% of accuracy in a testing set. The trained model is then applied on Hyperion imagery collected over an iron ore deposit. All the endmember spectra of this deposit are classified into either vegetation or any of the ores or rock present in the deposit. None of the endmembers is classified into non-iron ore minerals.     

Mapping hydrothermal alteration minerals using high-resolution AVIRIS-NG hyperspectral data in the Hutti-Maski gold deposit area,India

ABSTRACT

The present study exploits high-resolution hyperspectral imagery acquired by the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor from the Hutti-Maski gold deposit area, India, to map hydrothermal alteration minerals. The study area is a volcanic-dominated late Archean greenstone belt that hosts major gold mineralization in the Eastern Dharwar Craton of southern India. The study encompasses pre-processing, spectral and spatial image reduction using Minimum Noise Fraction (MNF) and Fast Pixel Purity Index (FPPI), followed by endmember extraction using n-dimensional visualizer and the United States Geological Survey (USGS) mineral spectral library. Image derived endmembers such as goethite, chlorite, chlorite at the mine site (chlorite mixed with mined materials), kaolinite, and muscovite were subsequently used in spectral mapping methods such as Spectral Angle Mapper (SAM), Spectral Information Divergence (SID) and its hybrid, i.e. SIDSAM_tan. Spectral similarity matrix of the target and non-target-based method has been proposed to find the possible optimum threshold needed to obtain mineral map using spectral mapping methods. Relative Spectral Discrimination Power (RSDPW) and Confusion Matrix (CM) have been used to evaluate the performance of SAM, SID, and SIDSAM_tan. The RSDPW and CM illustrate that the SIDSAM_tan benefits from the unique characteristics of SAM and SID to achieve better discrimination capability. The Overall Accuracy (OA) and kappa coefficient (?) of SAM, SID, and SIDSAM_tan were computed using 900 random validation points and obtained 90% (OA) and 0.88 (?), 91.4% and 0.90, and 94.4% and 0.93, respectively. Obtained mineral map demonstrates that the northern portion of the area mainly consists of muscovite whereas the southern part is marked by chlorite, goethite, muscovite and kaolinite, indicating the propylitic alteration. Most of these minerals are associated with altered metavolcanic rocks and migmatite.