New ASTER derived thermal indices to delineate mineralogy of different granitoids of an Archaean Craton and analysis of their potentials with reference to Ninomiya's indices for delineating quartz and mafic minerals of granitoids—An analysis in Dharwar Craton,India

We processed five thermal infrared (TIR) bands of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) “at-sensor radiance” (Level 1B) data to derive few new indices to delineate variation in quartz, feldspar and mafic minerals in three different variants of granitoid; commonly occurring quartz bearing intrusive rock group. In this regard, three indices named as quartz-bearing rock index (QRI), feldspar-bearing rock index (FRI) and mafic-bearing rock index(MRI) were proposed.QRI index was derived using band 10, band 12 and band 13((band 10/band 12) 1 (band 13/band 12)) of ASTER radiance image. MRI index was derived using band 12, band 13 and band 14 ((band 12/band 13) 1 (band 13/band 14)) of ASTER radiance bands while band 10, band 11 were combined to derive FRI ((band 10/band 11) index. Three indices were combined in false colour composite image (FCC) and three-dimensional scatter plot to delineate granite, alkali granite and mafic rich granodioritic gneiss from each other as these granitoids had variable abundances of quartz, feldspar and mafic minerals. QRI and MRI were compared with the corresponding quartz and mafic indices proposed by Ninomiya (2005). It was observed from the respective ratio images and their regression plots that MRI and Ninomiya's mafic index (NMI) were complementary to each other. On the other hand, QRI image was better in enhancing quartz enrichment in alkali granites than Ninomiya's quartz index (NQI).However, QRI index was comparable with the quartz index proposed by Rockwall and Hofstra (2008) in terms of delineating quartz enrichment in alkali granite. Mutual exclusive nature of mafic minerals and quartz in granitoids was also evident from the negative correlation between MRI and QRI indices of the granitoids. On the other hand, FRI and QRI were negatively correlated with low regression value. This was resulted due to the combined effect of inverse relation of abundance of two dominant feldspars with quartz in different granitoids. In granitoids, abundance of plagioclase is known to increase with decreasing quartz content in granodiorite and tonalite although alkali feldspar bearing granites are characterised with high silica content. Results of discrimination of granitoids using proposed indices were validated based on deriving emissivity spectra of rocks and comparing them with ASTER TIR band resampled laboratory spectra of respective granitoids in addition to use geological map of the study area. Emissivity spectra of granitoids were derived from emissivity image (derived using emissivity normalisation method) after geospatially tagging it with QRI–FRI–MRI image composite; which was used to delineate exposures of granitoids. Further, we also found that the QRI, MRI and FRI indices had poor temperature dependence; when these indices were compared with relative surface temperature image derived from radiance bands using emissivity normalisation algorithm. Therefore, proposed indices can be implemented for delineating mineralogical variations of granitoids irrespective of surface temperature condition. Hence, proposed indices may be used successfully to delineate different granitic intrusions and relating their mineralogical variations with metallogeny.     

结合实测光谱的ASTER TIR数据岩性划分与构造样式分析:以新疆阿克苏蓝片岩为例

常见造岩矿物的特征谱带位于热红外区域,因此热红外遥感在岩石地层划分与构造样式分析方面有巨大的应用潜力,并且精细岩石地层划分是构造样式分析的基础。新疆阿克苏蓝片岩被认为是目前世界范围内保存最好的前寒武纪蓝片岩之一。本文对该地质体中采集的不同类型岩石样品进行了室内热红外发射光谱测试,发现白云母石英片岩类残余辐射特征（restrahlen features,RF）位于波长8.55、9.16和9.60 μm处,绿泥绿帘片岩类RF位于波长9.60、10.50和11.66 μm处。按照ASTER TIR波段位置将样品的发射率光谱曲线重采样,利用ASTER TIR数据计算基性指数I_b和白云母指数I_m。依据I_b和I_m得到不同岩性段分布图,该图能反映蓝片岩地质体中不同基性程度岩石、后期侵入的基性岩墙群以及白云母石英片岩单元的空间分布。从岩性区域分布特征看,我们认为新疆阿克苏蓝片岩地质体平面构造样式表现为褶皱,其轴迹线为NE—SW向,这一结果与前人对其划分的单斜地层结构有较大的差异。另外,褶皱出现在地质体南部,说明其北部所受压力较南部小,与前人认识一致。研究结果体现了热红外遥感结合实测光谱可有效探测矿物岩石信息的优势,该方法可为相关研究提供参考。     

Study of land surface temperature and spectral emissivity using multi-sensor satellite data

In this study, an attempt has been made to estimate land surface temperatures (LST) and spectral emissivities over a hard rock terrain using multi-sensor satellite data. The study area, of about 6000 km², is a part of Singhbhum-Orissa craton situated in the eastern part of India. TIR data from ASTER, MODIS and Landsat ETM+ have been used in the present study. Telatemp Model AG-42D Portable Infrared Thermometer was used for ground measurements to validate the results derived from satellite (MODIS/ASTER) data. LSTs derived using Landsat ETM+ data of two different dates have been compared with the satellite data (ASTER and MODIS) of those two dates. Various techniques, viz., temperature and emissivity separation (TES) algorithm, gray body adjustment approach in TES algorithm, Split-Window algorithms and Single Channel algorithm along with NDVI based emissivity approach have been used. LSTs derived from bands 31 and 32 of MODIS data using Split-Window algorithms with higher viewing angle (50°) (LST1 and LST2) are found to have closer agreement with ground temperature measurements (ground LST) over waterbody, Dalma forest and Simlipal forest, than that derived from ASTER data (TES with AST 13). However, over agriculture land, there is some uncertainty and difference between the measured and the estimated LSTs for both validation dates for all the derived LSTs. LST obtained using Single Channel algorithm with NDVI based emissivity method in channel 13 of ASTER data has yielded closer agreement with ground measurements recorded over vegetation and mixed lands of low spectral contrast. LST results obtained with TIR band 6 of Landsat ETM+ using Single Channel algorithm show close agreement over Dalma forest, Simlipal forest and waterbody with LSTs obtained using MODIS and ASTER data for a different date. Comparison of LSTs shows good agreement with ground measurements in thermally homogeneous area. However, results in agriculture area with less homogeneity show difference of LST up to 2°C. The results of the present study indicate that continuous monitoring of LST and emissivity can be undertaken with the aid of multi-sensor satellite data over a thermally homogeneous region.     

ASTER mapping of gypsum deposits of Thumrait region of southern Oman

This study demonstrates the use of ASTER data for the mapping of gypsum deposits and associated geological formations that occurred in the Thumrait region of southern Oman. The measurement of spectra over samples of gypsum in the 1,300–2,500 nm wavelength using a PIMA spectrometer showed the presence of distinct absorptions at 1400–1600, 1750, 1940, 2,100, and 2,400 nm characteristics to O? H stretching, H₂O combinations, and S? O bending overtones and stretching, respectively. Studying the unique spectral absorption characters of gypsum samples, we developed a false color composite (FCC) and an image by decorrelation stretch using the spectral bands 7, 3, and 2 of ASTER. The results FCC showed the regions of gypsum occurrences, and the decorrelated image discriminated the gypsum occurrences from other geological formations of the area. The study of surface mineralogy of the region using the VNIR‐SWIR bands by the spectral angle mapper method showed the presence of sulfate, carbonate, and clay minerals of the geological formations in the study area. We compared the results of ASTER with the results obtained using spectral bands 12, 8, and 4 of Sentinel‐2A processed by the same methods. The study showed that the spectral bands of ASTER can be used for mapping the gypsum and associated geological formations.     

利用Aster数据估算Ca含量分布的研究

元素在地表的分布对矿产的赋存具有指示作用,而不同元素都有各自对应的光谱特征;使用光谱数据元素含量可快速、大面积提取元素分布信息,指导找矿工作。本文基于实地测量的岩石光谱发射率数据重采样至ASTER各热红外波段,然后进行波段比值处理;将波段比值与岩石中的Ca进行相关分析。使用SPSS软件做多元逐步回归,排除相关系数小及具有共线性的波段比值,得出Ca与发射率光谱的数值关系;通过数值关系计算,得到Ca含量的大致分布区域。结果表明,Ca含量与ASTER波段之间有较好的相关关系;利用ASTER波段反演地表岩石Ca含量是可行的;在Aster影像上Ca高含量地区与地层的岩性吻合度高。     

多源遥感数据图谱协同岩石单元分类方法

岩石单元的结构、构造、差异风化和出露状况在遥感图像上综合表现为图形纹理特征即“图”标志，其矿物成分和组合则表现为光谱特征即“谱”标志.传统遥感岩石单元分类以利用其光谱特征为主，图形纹理特征为辅，因此分类精度有限.以新疆维吾尔自治区与甘肃省交界的北山西段为研究区，开展岩石单元图形指数和光谱指数协同分类方法研究.基于Worldview-2全色图像构建的图形指数，能够量化岩石单元的层理、构造、展布形态和微地貌等特征，包括0°和45°定向滤波图像及灰度共生矩阵计算出的同质性和异质性特征图像、熵特征图像；光谱指数基于Worldview-2多光谱图像和ASTER（Advanced Spaceborne Thermal Emission and Reflection Radiometer）短波红外波段图像利用比值、和-差方法构建.多源遥感图像构建的光谱指数其光谱波段涵盖可见光-近红外及短波红外，包括RI（Ratio index）_ASTER、SI（Spectral index）_ASTER、SI_Worldview-2.采用面向对象方法对建立的图谱指数进行多尺度分割，依据不同岩石单元出露规模建立适宜的分割尺度，利用光谱指数自动提取相应岩石信息，实现岩石单元自动分类.结果表明，实验区基于图谱协同方法共划分出17类岩石单元，总体精度达到83.62%，而单独利用Worldview-2和ASTER图像，仅划分出13类和14类岩石单元.提出的图谱协同岩石分类方法可为我国西部高海拔深切割无人区地质调查及找矿工作提供新思路和遥感技术支撑.      

Investigation of a relation between radiogenic heat production and kinetic surface temperature from multispectral ASTER-TIR data: a case study on Elmissikat-Eleridiya granites,Central Eastern Desert,Egypt

In this paper, an attempt was tried to study the relation between radiogenic heat production rate (RHPR) that derived from gamma-ray spectrometric data and the kinetic surface temperature KST, which was calculated from the thermal emission and reflection radiometer-thermal infrared (ASTER-TIR) imagery applied on Elmissikat-Eleridiya district. This area is considered one of the most important uranium localities in the Central Eastern Desert of Egypt. The gamma-ray spectrometric data including both airborne data and in situ measurements concurrent with the collection of 20 rock samples were used to determine the rock density. The ground gamma-ray spectrometry has been conducted using GS-256 spectrometer at the same locations of rock samples. The gamma-ray spectrometric data (airborne and ground) beside rock density data were used for calculating RHPR. Alongside, pairs of daytime and nighttime ASTER-TIR images were collected and surface kinetic temperature for both day (daytime kinetic surface temperature (DKST)) and night (nighttime kinetic surface temperature (NKST)) were derived by using reference channel emissivity technique. The study showed a relative higher RHPR within syenogranite (4.2 up to 6 μW/m³) than other rock units. Besides, the KST of syenogranite ranged from 33 to 48 °C in daytime and between 7 and 17 °C at night. Comparing all results, no clear relation between RHPR and KST is evident. This is due to the very weak RHPR that is not sufficient to affect the surface heat temperature, which can be remotely sensed by ASTER satellite TIR data. This factor in addition to other factors such as: structural elements, topography, geographic locations, shading and scattering, rock moisture and density, can strongly affect the surface temperature. In conclusion, these results could be improved in areas of very high radioelement concentrations, especially ²³⁵U and through the use of the enhanced spatial resolution of future satellite TIR imaging instruments.     

ASTER数据在遥感蚀变填图中的应用研究——以内蒙古花敖包特银铅锌多金属矿床为例

花敖包特是位于内蒙古西乌珠穆沁旗的一个大型脉状银铅锌多金属矿床,其矿区的蚀变矿物主要是黏土矿物、绿泥石和方解石,此外还可见孔雀石、萤石和赤铁矿等局部蚀变矿化.结合花敖包特矿床的地质特征,本研究利用高级星载热辐射和反射探测器(ASTER)获取的遥感数据进行蚀变矿物填图.利用ASTER可见光-近红外波段和短波红外波段,对校正后遥感数据采用波段比值分析、波段组合分析和主成分分析来提取黏土矿物、绿泥石和方解石化蚀变.利用ASTER热红外波段,根据相关数值关系,对校正后遥感数据计算二氧化硅含量、QI值以及CI值来分析地质体二氧化硅含量变化规律和碳酸盐化蚀变.结合野外勘查结果发现,主成分分析、波段组合分析能够初步划分矿区绿泥石化、碳酸盐化和黏土化蚀变带以及硅化带,其中主成分分析方法取得的效果较好,显示矿区北部以绿泥石化带为主,南部以碳酸盐化和黏土化混合带为主,而热红外波段数值分析方法在矿田尺度下对矿区附近的硅化带和碳酸盐化蚀变也具有一定的识别能力.     

Integration of ASTER and landsat TM remote sensing data for chromite prospecting and lithological mapping in Neyriz ophiolite zone,south Iran

Chromite deposits in Iran are located in the ophiolite complexes, which have mostly podiform types and irregular in their settings. Exploration for podiform chromite deposits associated with ophiolite complexes has been a challenge for the prospectors due to tectonic disturbance and their distribution patterns. Most of Iranian ophiolitic zones are located in mountainous and inaccessible regions. Remote sensing approach could be applicable tool for choromite prospecting in Iranian ophiolitic zones with intensely rugged topography, where systematic sampling and conventional geological mapping are limited. In this study, Landsat Thematic Mapper (TM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data were used for chromite prospecting and lithological mapping in the Neyriz ophiolitic zone in the south of Iran. Image transformation techniques, namely decorrelation stretch, band ratio and principal component analysis (PCA) were applied to Landsat TM and ASTER data sets for lithological mapping at regional scale. The RGB decorrelated image of Landsat TM spectral bands 7, 5, and 4, and the principal components PC1, PC2 and PC3 image of ASTER SWIR spectral bands efficiently showed the occurrence of major lithological units in the study area at regional scale. The band ratios of 5/3, 5/1, 7/5 applied on ASTER VNIR‐SWIR bands were very useful for discriminating most of rock units in the study area and delineation of the transition zone and mantle harzburgite in the Neyriz ophiolitic complex. Spectral Angle Mapper (SAM) technique was implemented to ASTER VNIR‐SWIR spectral bands for detecting minerals of rock units and especially delineation of the transition zone and mantle harzburgite as potential zones with high chromite mineralization in the Neyriz ophiolitic complex. The integration of information extracted from the image processing algorithms used in this study mapped most of lithological units of the Neyriz ophiolitic complex and identified potential areas of high chromite mineralization (transition zone and mantle harzburgite) for chromite prospecting targets in the future. Furthermore, image processing results were verified by comprehensive fieldwork and laboratory analysis in the study area. Accordingly, result of this investigation indicate that the integration of information extracted from the image processing algorithms using Landsat TM and ASTER data sets could be broadly applicable tool for chromite prospecting and lithological mapping in mountainous and inaccessible regions such Iranian ophiolitic zones.     

基于ASTER数据的断裂构造判读:以甘肃白银地区为例

ASTER传感器提供了包括可见光-近红外（VNIR）、短波红外（SWIR）、热红外（TIR）共14个波段的地物波谱数据。其中最高分辨率在VNIR波段达到了15m。另外,在获得地物波谱数据的同时,它还能利用在03N波段和03B波段以不同视角获得的图像组成立体像对,从而获得同一地区的高程数据。这些特点为该数据的地质应用提供了很大的方便。由于断裂构造能造成断裂带内及其两侧之间地质环境与地貌特征的差异,这种差异会造成相应地区遥感影像中地物的波谱特征及空间分布即纹理型式上的差别。反之,使用多种图像处理技术,通过增强图像的灰度差并获取纹理图像,可以使这种差异凸现出来分析图像中的这些差异,找出在灰度和纹理上的规律性变化,不但可以推断可能的断裂分布,并可确定它的性质.利用ASTER数据高空间分辨率、多波谱段及同时提供DEM数据的特点,将之用于甘肃白银地区断裂构造的识别和判读。试验表明,利用该数据判读的结果与实地调查结果有相当的一致性。     

Retrieving of Land Surface Temperature Using Thermal Remote Sensing and GIS Techniques in Kandaihimmat Watershed,Hoshangabad, Madhya Pradesh

Remotely sensed thermal infrared (TIR) data have been widely used to retrieve land surface temperature (LST). LST is an important parameter in the studies of urban thermal environment and dynamics. In the study, an attempt has been made using LANDSAT 8 thermal imagery to compute LST and the associated land cover parameters viz; land surface emissivity (LSE), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and normalized difference water index (NDWI). Landsat 8 TIRS band 10 & 11 (thermal bands) during 21 Oct. 2016, 22 Nov.2016, 24 Dec. 2016 and 09 Jan. 2017 were processed for LST analysis. However, band 5 & band 4 of the imagery was processed for NDVI, band 6 & band 5 for NDBI and band 2 & band 5 for NDWI analysis. LST has been derived from both the bands 10 &11 and validated by in-situ observations on the date and time of satellite overpass from the study area. Band 10 derived LST have shown much temperature difference while comparing with the in-situ observations. However, LST derived from band 11 found similar & close to the in-situ measurements. Relationship between band 11 results and in-situ observed measurements were developed, which has showing a strong correlation with (r² = 0.991). Land surface emissivity were also evaluated which shows variation in different land cover surfaces like vegetation, settlement, forest cover and water body. The study has proven that land surface temperature derived from satellite band 11 is the actual surface temperature of the study area.     

Quartzose–mafic spectral feature space model: A methodology for extracting felsic rocks with ASTER thermal infrared radiance data

The original spectral features of felsic rocks are often intermingled with other surface objects, which results in difficulty of detecting felsic rocks using remote sensing techniques. Few felsic rock indices were proposed and visual interpretation with RGB false color composition is widely used to detect felsic rocks. This paper aims to construct a two-dimensional spectral feature space model to extract felsic rocks using ASTER thermal infrared radiance data. The study area is located in northern Qinghai Province, western China with average altitude of approximately 4200 m. A large number of training pixels of mafic–ultramafic rock, quartz-rich rock, felsic rock, carbonate rock and vegetation were selected from the ASTER images as samples of these surface objects. Then we used a quartz-rich rock index (QI, QI = band14 − 0.844 × band12 − 1.897) and a mafic–ultramafic rock index (MI, MI = 0.915 × band10 − band13 + 1.437) to generate a two-dimensional scatter plot. The plot was named after quartzose–mafic spectral feature space (QMFS). The samples show an approximate triangular shape in the QMFS. Mafic–ultramafic rock, quartz-rich rock and carbonate rock are located in separate locations in the three vertex regions, respectively, while felsic rock is located in the central region of the triangle. Next, we calculated a linear belt of silicate rocks in which silicate rocks vary regularly by using a linear regression analysis in the QMFS. Statistical characteristics of the felsic rock samples are analyzed. Afterwards, a polygon which delineates the distribution of felsic rock samples was constructed from the linear belt of silicate rocks. Then we generated a system of inequalities based on the equations of the edges of the polygon. The application of the inequalities to the ASER images shows a good performance of the QMFS for extracting felsic rocks.     

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。     

基于ASTER光谱特征的科技廊带岩性填图:以新疆塔什库尔干地区为例

科技廊带填图是以解决关键地质问题为目的填图方式,但部分地区海拔高差大,交通不便,给填图工作造成巨大困难。遥感岩性解译可为填图工作提供重要参考。然而,当前主流的遥感岩性解译方法仍是基于地貌纹理等间接解译标志开展的。相对而言,矿物岩石光谱特征作为最为直接和准确的遥感岩性解译标志却少有实例报道。本文基于ASTER遥感影像和岩石光谱特征分析,对部分地区海拔高差较大的新疆塔什库尔干地区进行岩性解译工作,以检验其适用性。在野外工作对研究区岩性类型进行识别和鉴定的基础上,ASTER光谱分析成果影像可较准确显示区内主要岩性类型的地表出露。其中,ASTER热红外波段比可反映区内中高级变质岩、花岗岩类及碳酸盐岩的整体分布特征;在此基础上,ASTER可见光-近红外及短波红外波段比可准确鉴定与Fe~(3+)、Fe~(2+)-硅酸盐、Al-OH、Mg-OH等成分相关的矿物组成(如绿泥石、白云母及石榴子石等),从而对地表岩性出露进行更为细致的识别和分类。研究结果表明基于ASTER光谱特征的岩性填图方法在新疆、西藏等地区有天然的实用性,既可克服区内海拔高、交通不便等困难,又可准确指示地表关键岩性类型的出露情况,可作为科技廊带填图及地质研究工作的重要手段。     

ASTER数据在浅覆盖区蚀变遥感异常信息提取中的应用——以新疆西准噶尔包古图斑岩铜矿岩体为例

遥感卫星的多光谱数据应用于找矿已取得显著成效,2004年7月中国卫星地面站开始提供ASTER（Advanced Spaceborne Thermal Emission and Reflection Radiometer,高级星载热发射反照辐射计）数据,因涵盖波长范围宽［VNIR（Visible and Near Infrared）、SWIR（Short wavelength Infrared）、TIR（Thermal Infrared）］、波段多（14个波段）、性价比合理等因素,ASTER数据的研究迅速发展。长久以来,对覆盖区进行蚀变遥感异常信息提取一直是遥感找矿的关注点之一。笔者等利用ASTER数据对浅覆盖区——包古图斑岩铜矿的Ⅱ号、Ⅴ号斑岩体进行蚀变遥感异常提取,提取的蚀变异常与野外地质情况吻合性好。分别提取了光谱特征谱带差异明显的2组蚀变矿物的异常信息：第一组是蒙脱石、埃洛石、伊利石与绢云母;第二组是方解石、黑云母与绿泥石。提出了需要进一步工作的异常靶区。     

PCA and SVM as geo-computational methods for geological mapping in the southern of Tunisia,using ASTER remote sensing data set

The purpose of this study was to examine the efficiency of Advanced Space Borne Thermal Emission and Reflection Radiometer (ASTER) data in the discrimination of geological formations and the generation of geological map in the northern margin of the Tunisian desert. The nine ASTER bands covering the visible (VIS), near-infrared (NIR) and short-wave infrared (SWIR) spectral regions (wavelength range of 400–2500 nm) have been treated and analyzed. As a first step of data processing, crosstalk correction, resampling, orthorectification, atmospheric correction, and radiometric normalization have been applied to the ASTER radiance data. Then, to decrease the redundancy information in highly correlated bands, the principal component analysis (PCA) has been applied on the nine ASTER bands. The results of PCA allow the validation and the rectification of the lithological boundaries already published on the geologic map, and gives a new information for identifying new lithological units corresponding to superficial formations previously undiscovered. The application of a supervised classification on the principal components image using a support vector machine (SVM) algorithm shows good correlation with the reference geologic map. The overall classification accuracy is 73 % and the kappa coefficient equals to 0.71. The processing of ASTER remote sensing data set by PCA and SVM can be employed as an effective tool for geological mapping in arid regions.     

基于多源遥感数据的高山峡谷区岩性信息提取研究——以新疆乌什县北山1:50000填图试点为例

新疆乌什县北山1:50000填图试点项目位于塔里木盆地西北边缘和西南天山交接部位,海拔较高,地形切割较深,属于典型的高山峡谷区。利用ASTER、SPOT6、GF-2等多源遥感数据,基于典型岩性光谱吸收特征,进行岩性差异信息增强与提取研究,总结出一套基于多源遥感数据进行岩性单元边界划分的方法。以ASTER数据、ASTER与SPOT6协同数据、ASTER与GF-2协同数据等为基础影像数据,并选择最佳波段组合进行RGB彩色合成,从而增强影像差异,结合已有研究区地质资料,初步圈定不同影像单元边界;继而利用矿物丰度指数、SMACC端元丰度提取等方法识别研究区内主要岩性的分布位置和范围;最后结合野外实际调查数据,依据实际地质背景和影像质量进行筛选,获得最终的岩性单元解译图。研究结果为该区进一步进行地层优化划分及对比提供了参考资料。      

ETM+和ASTER数据在遥感矿化蚀变信息提取应用中的比较——以安徽铜陵凤凰山矿田为例

在利用遥感技术找矿中,矿化蚀变信息识别与提取起着重要作用。选择具有典型蚀变特征的安徽铜陵凤凰山矿田作为研究区,从分析地物波谱,尤其是岩矿光谱特征出发,根据ETM+和ASTER数据的光谱特征,采用主成分分析（PCA）,设计了相应的粘土矿化蚀变信息提取方案,成功地进行信息提取。对两者的提取结果进行比较后表明,ASTER数据较之ETM数据在粘土类矿化蚀变信息提取中具有更大的优势。     

ASTER Spectral Analysis for Host Rock Associated with Porphyry Copper-molybdenum Mineralization

This study is an attempt to understand the application of spectral image processing methods to ASTER data for mapping host rock associated with porphyry copper-molybdenum mineralization. The application of remote sensing in identifying variations in surface mineralogy, structural elements, and lithologic contacts can help in identifying such relations. Signatures collected from the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) data is used to map the host rock of Zafarqand area. The study area is located in the central segment of the Urumieh–Dokhtar volcanic belt of Iran. The Urumieh-Dokhtar is a potential zone for exploration of new porphyry copper deposits. Band ratio, band math, false colour composites and principal component analysis techniques are used to refine the different lithologic units in the area. These methods showed the discrimination of acidic igneous rock from intermediate igneous rock and the boundary between igneous rocks using the shortwave infrared bands (SWIR) of ASTER at regional scale. Results have proven to be effective and in accordance with the results of field observations, ore microscopy examination and with reference geological map. In conclusion, the image processing methods used can provide cost-effective information to discover possible locations of porphyry copper and epithermal gold mineralization prior to detailed and costly ground investigations. The extraction of spectral information from ASTER data can produce comprehensive and accurate information for copper and gold resource investigations around the world, including those yet to be discovered.     

新疆西准噶尔包古图斑岩铜矿蚀变岩石的光谱特征及其意义

地物的光谱特征是遥感识别地物的主要依据,不同地物的反射光谱具有其特定的吸收特征谱带。利用ASD和PIMA反射光谱测试仪对新疆西准噶尔包古图斑岩铜矿Ⅱ号、Ⅴ号斑岩铜矿岩体的蚀变围岩(地表采样与钻井采样)进行测试,并对结果进行分析总结。根据反射光谱特征谱带获得蚀变矿物的种类,确定了岩体的蚀变矿物组合,得到反射光谱的吸收谷在ASTER数据中所处的波段;对反射光谱曲线进行数学积分,获得ASTER数据中的强吸收波段。将以上2种分析得到的吸收性波段组合应用于蚀变遥感异常信息提取,结果表明蚀变遥感异常与野外地质特征吻合程度较高。反射光谱分析表明确定岩石矿物的反射光谱特征谱带是进行遥感信息提取工作的前提,波段组合选取对提取蚀变遥感异常信息非常重要。