Application of Landsat-8 and ASTER satellite remote sensing data for porphyry copper exploration: a case study from Shahr-e-Babak,Kerman, south of Iran

Abstract

The Shahr-e-Babak region located in the Kerman metallogenic belt is one of the high potential segments of Urumieh–Dokhtar magmatic arc for porphyry copper and epithermal gold mineralization in the south of Iran. This high potential zone encompasses several porphyry copper deposits under exploitation, development and exploration stages. The aim of this study is to evaluate Landsat-8 data and comparison with the Advanced Spaceborne Thermal Emission and Reflection Radiometer data-sets for mapping hydrothermal alteration zones related to Cenozoic magmatic intrusions in Shahr-e-Babak region. Previous studies have proven the robust application of ASTER in lithological mapping and mineral exploration; nonetheless, the Landsat-8 data have high capability to map and detect hydrothermal alteration zones associated with porphyry copper and epithermal gold mineralization. In this investigation, several band combinations and multiplications, developed selective principal component analysis and image transformations were developed for discriminating hydrothermal alteration zones associated with porphyry copper mineralization using Landsat-8 data.     

陆地卫星TM及JERS-1卫星SAR数据用于西藏东部斑岩铜矿勘查

本文介绍了利用陆地卫星TM及JERS-1卫星SAR数据在西藏东部地区进行斑岩铜矿勘查项目的早期研究成果。文中通过对现有地质资料的分析认为,研究区内的矿化作用除受三叠系火山岩建造控制外,还与喜山期的中酸性侵入体有关。而陆地卫星TM图像的解译结果表明,区内的主要矿床几乎都分布在与三叠纪古火山机构相关的环形构造内。为了增强和提取出与斑岩铜矿化有关的蚀变岩信息,研究中采用了对数残差、矿物指数和HSI变换等方法对陆地卫星TM及JERS-1卫星SAR数据进行了处理与分析,所提取出的蚀变信息与目视解译所发现的环形构造位置极为吻合。实践证明,遥感图像上的环形影像及蚀变岩石信息对矿产勘查有指示价值。     

斑岩型铜矿找矿预测中环形构造的示矿作用——以玉龙—马拉松多子区为研究区

在斑岩型铜矿资源潜力评价中,斑岩体是圈定铜矿最小找矿预测区的重要依据。研究表明,遥感图像上的许多环形影像与岩浆活动(包括斑岩体)有关。为了快速进行斑岩型铜矿成矿预测,利用遥感技术在西藏玉龙—马拉松多斑岩型铜矿周边地区开展了找矿预测。首先建立了环形构造的遥感解译标志;然后开展了环形构造的解译工作,研究了该区环形构造的展布特征;最后总结了由环形构造推断斑岩体的标志。结果表明,遥感解译的环形构造为该区斑岩型铜矿最小找矿预测区的圈定提供了重要依据。     

Selecting optimum base wavelet for extracting spectral alteration features associated with porphyry copper mineralization using hyperspectral images

Extracting a set of meaningful spectral features could enhance the classification performance. This is particularly important in hyperspectral images where the dataset are very large and time consuming to process. Wavelet transform as a powerful decomposition tool in both low and high frequency components could play an essential role in extracting spectral features of target minerals. Selecting the optimum base wavelet is an important step in wavelet transform. In this research, two criteria to select optimum base wavelet were implemented on three wavelet series including Daubechie (db), symlet (sym) and coiflet (coif). Energy criterion involves entropy factor and energy-to-Shannon entropy ratio while matching shape criterion operates according to correlation coefficients. High ranking base wavelets in both energy and shape criteria, coif1, db3 and db7, are recommended to be utilized in hyperspectral image classification. Neural Network technique was used for classification and trained by means of mineral spectral features related to typical porphyry copper deposits. Non-Linear wavelet feature extraction was employed to select the efficient features as input data. The study area covered by Hyperion data contains two well-known porphyry copper deposits, Darrehzar and Sarcheshmeh, located in the Iranian copper belt. Based on classification error matrix, it is concluded that db7 through 12 selected features exhibits the maximum consistency with the field measured data and can be recommended as an appropriate base wavelet for detecting porphyry copper deposits.     

Alteration Mapping for Porphyry Copper Exploration Using ASTER and QuickBird Multispectral Images,Sonajeel Prospect,NW Iran

The Sonajeel prospect is located in the Arasbaran belt which is one of the significant copper mineralization belts in NW Iran. There are mostly Eocene volcano-sedimentary rocks and Post Eocene intrusive units which are the source for mineralization in the area. ASTER multispectral images were used for delineation of alteration zones as a key feature of porphyry copper mineralization. Due to the need for geometric correction and ortho-rectification of the ASTER images, a high resolution QuickBird image with pixel width of about 60 cm (in PAN) was employed as a reference image in order to boost the rectification process. Ortho-rectification has been done by using digital elevation model which is created by topographic map in scale 1:1000. Potassic alteration as one of the essential alteration types in porphyry copper deposits, distributed mostly in the north of the Sonajeel prospect that determined by Thermal infrared bands processing. Phyllic and argillic alteration zones detected by creating relative absorption band-depth grids which are comparable to field observations. Moreover, silica rich areas which are remnants of hydrothermal circulation and form at the top of porphyry copper systems were detected for recognition of epithermal deposits (with 1 km distance from Sonajeel porphyry system). Finally, Remote Sensing results were compared by field evidences especially for determination of an epithermal system. Most parts of the alteration zones were observed of the surface confirmed with the remote sensing alteration (in average about 75% matched fittingly), displayed concentrations anomalous in the NE and NW parts of the studied area.     

Hydrothermal Alteration Mapping Using ASTER Data for Reconnaissance Porphyry Copper Mineralization in the Ahar Area, NW Iran

The Ahar area is located in East Azarbaijan province, and covers an area of about 2,500 km². Spectral mapping techniques were applied on VNIR and SWIR of ASTER data for discriminating between hydrothermal alteration zones and the identification of high potential mineralized lithological unit associated with hydrothermal porphyry copper mineralization in the Ahar. In this research to remove atmospheric and topographic effects from ASTER data, the log-residual method (LRM) was used. Four methods, Relative Band Depth Ratios (RBD), Principal Component Analysis (PCA), Minimum Noise Fraction (MNF) and matched filtering (MF), were used to processing and interpretation of remote sensing data in the study area. Results show that ASTER images provide preliminary mineralogy information and geo-referenced alteration maps at low cost and with high accuracy for reconnaissance porphyry copper mineralizations.     

A general framework of TOPSIS method for integration of airborne geophysics,satellite imagery,geochemical and geological data

This work presents the promising application of three variants of TOPSIS method (namely the conventional, adjusted and modified versions) as a straightforward knowledge-driven technique in multi criteria decision making processes for data fusion of a broad exploratory geo-dataset in mineral potential/prospectivity mapping. The method is implemented to airborne geophysical data (e.g. potassium radiometry, aeromagnetic and frequency domain electromagnetic data), surface geological layers (fault and host rock zones), extracted alteration layers from remote sensing satellite imagery data, and five evidential attributes from stream sediment geochemical data. The central Iranian volcanic-sedimentary belt in Kerman province at the SE of Iran that is embedded in the Urumieh–Dokhtar Magmatic Assemblage arc (UDMA) is chosen to integrate broad evidential layers in the region of prospect. The studied area has high potential of ore mineral occurrences especially porphyry copper/molybdenum and the generated mineral potential maps aim to outline new prospect zones for further investigation in future. Two evidential layers of the downward continued aeromagnetic data and its analytic signal filter are prepared to be incorporated in fusion process as geophysical plausible footprints of the porphyry type mineralization. The low values of the apparent resistivity layer calculated from the airborne frequency domain electromagnetic data are also used as an electrical criterion in this investigation. Four remote sensing evidential layers of argillic, phyllic, propylitic and hydroxyl alterations were extracted from ASTER images in order to map the altered areas associated with porphyry type deposits, whilst the ETM+ satellite imagery data were used as well to map iron oxide layer. Since potassium alteration is generally the mainstay of porphyry ore mineralization, the airborne potassium radiometry data was used. The geochemical layers of Cu/B/Pb/Zn elements and the first component of PCA analysis were considered as powerful traces to prepare final maps. The conventional, adjusted and modified variants of the TOPSIS method produced three mineral potential maps, in which the outputs indicate adequately matching of high potential zones with previous working and active mines in the region.     

基于MapGIS图元参数检索开发与应用

根据GIS空间数据包含的信息:①空间定位数据;②属性数据;③空间图元信息。把数据检索进行重新分为空间检索、属性检索和空间图元参数检索等3类,并利用Visual basic6.0+Map GIS6.5二次开发函数库设计和开发出图元参数条件查询模块。该模块是空间检索和属性检索的有益的补充,且界面友好,可以有效地通过空间实体的图元参数进行数据检索,并应用于西藏冈底斯斑岩铜矿预测评价中,成功地通过图元参数检索提取了岩浆岩、断裂构造等有用信息。     

朱诺斑岩型铜矿床外围遥感找矿预测

基于ETM+遥感数据源,利用ENVI遥感图像处理软件对云、雪被、第四系、水体、阴影等进行了掩膜;采用特征主成分分析技术对西藏自治区朱诺斑岩型铜矿床及其外围地区开展遥感羟基和铁染矿化蚀变信息提取,并进行了地质解译。据此圈定找矿远景区,为朱诺铜矿床外围地区开展找矿工作提供了先决条件。     

西藏多不杂斑岩铜矿ASTER遥感蚀变异常特征

采用ASTER数据,利用"掩模+定向主成分分析"方法提取了多不杂斑岩铜矿的遥感蚀变异常。对蚀变异常的特征、蚀变异常与地面蚀变对应关系、蚀变异常与已知矿体的关系等几个方面进行了初步探讨,认为利用ASTER数据提取的蚀变异常效果较好,为西藏自治区矿产资源潜力评价多龙铜矿预测工作区的最小预测区圈定提供了遥感依据。     

大型斑岩铜矿的遥感信息探讨

遥感影像解译的不同规模级别的线性构造、不同类型的环形构造和线-环组合类型以及色彩异常影像是寻找斑岩铜矿,特别是大型斑岩铜矿床最有用的遥感标志。1.砂岩铜矿的规模直接与不同规模不同级别的线性构造相联系区域性斑岩铜矿带直接受大型区域线性构造带和它们的汇聚格局控制,这种区域线性构造带多为区域压性壳断裂或超壳断裂,在遥感图像上常显示为浅色带,其长度超过100km,被称为主干边缘线性构造带(处于隆起单元向坳陷单元过渡部位,靠近隆起单元一侧).此外,一系列次级线性构造往往与主干边缘线性构造成一定角度相交,共同形成一种贯通性构造,在遥感图像上也常显示为浅色线;并直接控制斑岩铜矿田的分布和矿床的定位,被称为横向线性构造,长度一般1km-100km,主要包括三种类型(略),均显示张性特征。事实上,与斑岩铜矿有关的蚀变矿化直接受控于更低级别的线性构造(断裂和裂隙),它们常构成统一的环状和放射状断裂、裂隙系统。2.不同组合的多层环形影像是斑岩铜矿的不同呈矿环块构造的映像几乎所有的斑岩铜矿都与环块构造有关,特别是Ⅲ或Ⅳ级环块(直径50km-500km,包括环隆、环陷及褶皱-断裂环块等).它们控制了斑岩铜矿的定位。     

基于穷举法的高光谱遥感图像地物识别研究

介绍了一种基于穷举法的高光谱遥感图像地物识别方法.该方法从所有与研究区有关的可能参考光谱中识别出图像上每个像元的最佳匹配光谱,绘制识别结果图,并由图中信息可对参考光谱进行更换,以求得最佳识别结果.并以云南省中甸普朗斑岩铜矿区外围的高光谱遥感图像为例,得到了该区的地物识别图,经实地检验,证实了该方法的有效性.     

Ontology-based integration of topographic data sets

The integration of topographic data sets is defined as the process of establishing relationships between corresponding object instances in different, autonomously produced, topographic data sets of the same geographic space. The problem of integrating topographic data sets is in finding these relationships, considering the differences in content and abstraction. A conceptual framework is developed. Components of this framework are ontologies and sets of surveying rules. New in this approach is the introduction of a reference model. A reference model belongs uniquely to the combination of topographic data sets to be integrated. The framework is tested on two topographic data sets with area instances (polygons) which have crisp and complete boundaries and are not displaced for cartographic reasons. The overall conclusion is that the ontology-based framework is feasible, if (1) there is (at least partial) knowledge of the surveying rules, and (2) the data sets can be synchronized in time. The application of this framework is most suitable for object classes with instances that are easy to identify and have a limited spatial extent (e.g., buildings).     

Evaluating the effect of spatial subsetting on subpixel unmixing methodology applied to ASTER over a hydrothermally altered terrain

This study investigates the effect of spatial subsets of Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) L1B visible-near infrared and short wave-infrared (VNIR-SWIR) data on matched filtering results at the central part of Kerman magmatic arc, where abundant porphyry copper deposits exist. The matched filtering (MF) procedure was run separately at sites containing hydrothermal minerals such as sericite, kaolinite, chlorite, and jarosite to map the abundances of these minerals on spatial subsets containing 100, 75, 50, and 25 percent of the original scene. Results were evaluated by comparing the matched filtering scores with the mineral abundances obtained by semi-quantitative XRD analysis of corresponding field samples. It was concluded that MF method should be applied to the whole scene prior to any data subsetting.     

A Novel Remote Sensing Image Classification Scheme Based on Data Fusion, Multiple Features and Ensemble Learning

In this paper, we propose a novel scheme to improve the accuracy of remote sensing image classification by integrating data fusion, multiple feature combination and ensemble learning. Intensity-Hue-Saturation (IHS), Gram-Schmidt (GS), Brovey and wavelet fusion methods are first performed to obtain the optimal fusion images of high resolution and multispectral images. Support Vector Machine (SVM) classifier is then adopted to classify the fused image with different feature sets, and ensemble learning algorithm based on dynamic classifier selection (DCS) is finally used to integrate multiple classification maps. The proposed classification scheme is implemented with three remote sensing data sets, obtaining the highest overall accuracy and kappa coefficient in all cases (92.63% and 0.8917 for BJ-1 data set, 81.89% and 0.7513 for Landsat TM and SPOT4 data set, 92.21% and 0.8838 for ALOS data set respectively). The experimental results show that the integration of data fusion, feature combination and ensemble learning improves the classification performance obviously and has great potential in practical uses.     

基于矿物光谱指数的蚀变信息提取——以西藏多龙铜金矿集区ASTER数据为例

矿物光谱指数是利用比值的方法增强Fe和含OH矿物在可见光、短波红外区间的吸收特征,进而提取蚀变矿物信息的一种方法。由于斑岩型矿床的蚀变分带特征明显,西藏多龙矿集区中集中了斑岩型、浅成低温热液型等铜、金矿床,通过矿物光谱指数的计算提取相关蚀变信息,对该区域的下一步找矿具有指导意义。本文采用矿物光谱指数(5+7)/6、(6+9)/8等方法提取了镁、铝两类羟基及铝羟基类下的高岭石等蚀变信息,采用5/4、2/1的方法提取了二价铁、三价铁的蚀变信息。经过与OLI影像采用PCA方法及野外实地勘查采样,证实了利用本文方法所提取的蚀变信息有效。     

Data Integration Issues for a Farm Decision Support System

This paper explores data integration and compatibility issues raised during the development of a prototype spatial decision support system (SDSS) as a support tool for the farm manager of the University of Central Lancashire's farm at Newton Rigg and as a teaching resource for staff and students on campus. Metadata concerns and interoperability problems are addressed in detail. The paper outlines the proposed model for the SDSS and issues identified during the investigation of the users’ requirements and the analysis of the underlying spatial data sets. The initial data issues relate to the identification of existing and missing data sets ( Parker et al. 1996 ) and the creation of metadata describing the data sets. The second area to be explored concerns interoperability issues. This is relevant when users must access more than one dataset using distributed computing resources ( Sondheim et al. 1999 ).     

Harnessing the power of immersive virtual reality - visualization and analysis of 3D earth science data sets

ABSTRACT

The availability and quantity of remotely sensed and terrestrial geospatial data sets are on the rise. Historically, these data sets have been analyzed and quarried on 2D desktop computers; however, immersive technologies and specifically immersive virtual reality (iVR) allow for the integration, visualization, analysis, and exploration of these 3D geospatial data sets. iVR can deliver remote and large-scale geospatial data sets to the laboratory, providing embodied experiences of field sites across the earth and beyond. We describe a workflow for the ingestion of geospatial data sets and the development of an iVR workbench, and present the application of these for an experience of Iceland’s Thrihnukar volcano where we: (1) combined satellite imagery with terrain elevation data to create a basic reconstruction of the physical site; (2) used terrestrial LiDAR data to provide a geo-referenced point cloud model of the magmatic-volcanic system, as well as the LiDAR intensity values for the identification of rock types; and (3) used Structure-from-Motion (SfM) to construct a photorealistic point cloud of the inside volcano. The workbench provides tools for the direct manipulation of the georeferenced data sets, including scaling, rotation, and translation, and a suite of geometric measurement tools, including length, area, and volume. Future developments will be inspired by an ongoing user study that formally evaluates the workbench’s mature components in the context of fieldwork and analyses activities.     

Assessment of Land Surface Subsidence Due to Underground Metal Mining Using Integrated Spaceborne Repeat-Pass Differential Interferometric Synthetic Aperture Radar (DInSAR) Technique and Ground Based Observations

Differential interferometric synthetic aperture radar (DInSAR) is a novel remote sensing technique to measure earth surface deformation. It is capable of obtaining dense information related to the deformation of a large area efficiently, economically and effectively. Therefore, DInSAR is a promising technology for monitoring the earth surface deformation related to some natural hazardous events, such as earthquake, volcano eruption, land subsidence, landslide. In present study, Conventional DInSAR technique have been applied to a mineral rich zone, coming under the Khetri copper belt, a part of Northern Aravali range of hillocks in India, predominant with mining activities since late 1960’s to address the possibility of deformation phenomena due to hard rock underground metal mining. Four interferometric SAR data sets of Radarsat-2 was used for the study area to address the subsidence/uplift phenomena. Further, results obtained from conventional DInSAR technique using Radarsat-2 data sets compared with results obtained from ground based observation technique for its validity. In both the techniques, deformation results obtained in terms of average subsidence rate in mm (quarterly basis) of points under study within mining zone of Mine-A has well agreed to each other. Further, it has been observed that average subsidence rate in mm (quarterly basis) obtained from space based observation and ground based observation are 5.6 and 6.67, respectively over the points under study in mining zone of Mine-A.     

Ramgarh crater,Rajasthan, India: Study of Multispectral images obtained by Indian remote sensing satellite (IRS‐IA)

Ramgarh Crater, Rajasthan, India is a potential impact crater that has not been studied so far. The proximity of Ramgarh Crater to the Deccan flood basalt terrain makes it important to examine the spatial and temporal relationship of this crater to Deccan Volcanism because recent studies propose a strong link between impact cratering and major flood basalt eruptions. A detailed multidisciplinary study is necessary to evaluate the structure and lithology of Ramgarh Crater and its temporal relationship to the emplacement of Deccan eruptions in India .Application of the IRS‐IA data to study the lithologic/surface characteristics of Ramgarh Crater (attempted for the first time) indicates the potential application of remote sensing data in these studies. The IRS‐IA data are of good quality and resolution. Our preliminary assessment has shown that these data are helpful in generating lithology soil vegetation profiles of Ramgarh Crater region. These “profile maps” would be useful for targeting the specific areas in the region for a closer look and ground truth verification during the field work and sample collection in the region.