运用LANDSAT ETM+和ASTER数据进行岩性分类

本文评价了运用ASTER和LANDSAT ETM+数据进行岩性制图的性能。分别利用ASTER数据不同波段区图像及其组合,以及ETM+数据进行岩性分类,并探讨了将ASTER和ETM+数据叠加在一起进行了岩性分类; 利用现有地质图对所有分类结果进行了定量评价。结果表明,ASTER数据不同波段的岩性识别能力不同,并且较ETM+数据能更准确地识别岩性。更重要的是,把ASTER与ETM+数据结合在一起进行岩性分类,可获得比用任一数据单独分类更高的分类精度,表明二者的光谱特征具有一定的互补性。     

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.     

基于MODIS数据的朝鲜半岛土地利用变化信息提取

以朝鲜半岛为研究区域, 基于2000年和2007年的MOD IS数据, 应用线性光谱混合模型进行像元组分分解并提取分类特征, 对像元组分分解后有错分的地物类型结合纹理进行分析, 以决策树模型进行土地利用分类。结果表明, 像元组分分解后的决策树分类结果总体精度达78.346 5% , Kappa系数达0.681 3。与像元组分分解前最大似然法和决策树分类结果相比, 决策树分类精度优于最大似然法, 且像元组分分解方法提高了分类精度。经2000年和2007年像元组分分解后的决策树分类结果对比: 朝鲜耕地面积增加; 韩国耕地面积减少, 居民地面积增加。     

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.     

Assessment of the reliability of supervised classifications of Landsat-7, ASTER,and SPOT-5 multispectral data in rock unit discriminations of Jabal Daf-Wadi Fatima area,Saudi Arabia

Multispectral, multiresolution remotely sensed data were processed to emphasize geological interpretation of Jabal Daf-Wadi Fatima area. The investigated area is situated in the central western part of Saudi Arabia and geologically consists of igneous and metamorphosed rocks overlain by sedimentary sequence belonging to the Arabian-Nubian Shield. Three sets of digital satellite data, Landsat-7 ETM+, ASTER, and SPOT-5, were used in this study. The application of image processing techniques enables to identify and delineate the lithologic units and the structural features of the study area. The results of this study indicate that the confusion matrix of the three maximum likelihood supervised classifications of the three datasets shows that the Landsat ETM+ bands scored the best degree of average and overall accuracy (77 and 78%, respectively). This classification distinguishes most of the rock units for mapping in the investigated area. The supervised classification of ASTER and SPOT bands has lower degrees of accuracy than the classified Landsat data. The supervised classification of SPOT bands has a degree of average and overall accuracy of 66 and 67%, respectively, but it is the best for distinguishing the spectral signatures of the different members of Fatima Formation (lower, middle, and upper members). The statistical analyses of the confusion matrices of classifications and the interpretation of the produced classified thematic maps revealed that the classification accuracy does not necessary depend on the spatial resolution of satellite data. The data of the highest spatial resolution such as SPOT data are also very useful in emphasizing and classifying the rock units of a small outcrop area. The detailed geological map of Jabal Daf-Wadi Fatima area is interpreted in this work from supervised classified images of different resolutions as well as the structure map of this area. This study shows that it is preferable to use the supervised classifications of multiresolution data for rock unit discrimination in detailed field mapping.     

南美典型铁矿床遥感找矿模型研究

针对南美地区两种典型铁矿—苏比利尔湖型和阿尔果玛型铁矿,基于ETM+遥感数据,采用光谱角方法提取研究区的羟基、铁染蚀变信息;通过影像增强,波段合成等预处理结合人工解译,进行赋矿地层和控矿构造信息提取。总结分析示矿信息规律和特征,建立遥感找矿模型,圈定2处遥感找矿靶区,缩小了野外地质调查范围。     

多种类植被覆盖地区ASTER影像岩石、土壤信息提取方法研究

植被的发育限制了遥感在地质学方面的应用,特别是在多种类植被发育地区不能直接地根据波谱特征进行岩石与矿物方面的填图.利用线性波谱分离等技术方法可以从植被、基岩或土壤混合信息中区分出多类别植被波谱,从像元混合光谱中减去各植被类型所占的像元光谱强度,从而可以求出土壤光谱强度及其所占的份额,有效剥离出岩石和土壤信息.在试验区利用多种类植被干扰消除方法,进行遥感蚀变矿物和岩石填图,具有极大的可靠性.该技术可以在中等植被发育地区的遥感填图中得以推广和应用.     

Endmember orthonormal mapping in hyperspectral mixture analysis to address endmember variability

Spectral unmixing estimates the abundance of each endmember at every pixel of a hyperspectral image. Each material in traditional unmixing algorithms is represented through a constant spectral signature. However, endmember variability always exists due to environmental, atmospheric, and temporal conditions, which leads to poor accuracy of the estimated abundances. This paper proposes a new unmixing algorithm based on a new linear transformation called endmember orthonormal mapping (EOM) to overcome the aforementioned problem. The EOM transformation maps original spectral space to a new EOM space to reduce endmember variability. In the original spectral space, each material is represented by a set of spectra (endmember set) which is extracted using the automated endmember bundles (AEB) method. The EOM transforms each endmember set to a vector in the EOM space so that these vectors are orthonormal. On account of orthonormalized endmembers, the condition number of the mixing matrix in the EOM space reduces. Furthermore, we consider the noise term as an additional virtual endmember set mapped to a vector that is orthogonal to other endmembers. As a result, a promising unmixing accuracy is obtained through applying the least squares abundance estimation in the subspace orthogonal to noise. Experimental results of both synthetic and real hyperspectral images demonstrate that the proposed algorithms provide much enhanced performance compared with the state-of-the-art algorithms.     

Utilization of supervised classification in structural and lithological mapping of Wadi Al-Marwah Area,NW Arabian Shield,Saudi Arabia

Wadi Al-Marwah area is located in the northwestern part of the Arabian Shield, Saudi Arabia. It is mainly covered by Precambrian igneous and sedimentary rock units. This area was not subjected to previous detailed lithological or structural mapping. This study aims to apply supervised classification technique of remotely sensed digital satellite data of Landsat 7 for detailed lithological and structural mapping of the area. The fusion between multispectral Enhanced Thematic Mapper (ETM)+ data and high-resolution panchromatic ETM+ band-8 produced a color composite fused image for the study area, scale 1:50,000. The structural lineaments of the study area were extracted and interpreted from the digital imageries data. Little discrepancies or improvements were detected when combining the supervised classification results with the Landsat ratios or principal component analysis. These highlighted the benefits of multispectral classification, especially in terms of lithologic discrimination. The overall results of image processing techniques, applied in this work, were excellent and succeeded in the performance of a more detailed and accurate lithological and structural maps (scale 1:50,000) than the previous published maps for the investigated area.     

基于光谱匹配的热红外高光谱数据岩性分类研究

从岩石光谱出发,结合光谱谱带强度特征和光谱波形特征,针对机载热红外高光谱数据（TASI）,在以往算法基础上,提出一种改进的算法--光谱离散能级波形匹配法（SDEM）,并将其运用到岩性分类研究中。SDEM算法能识别岩石光谱间的微小差异,并在充分考虑光谱谱带强度和波形特征的同时,有效减弱数据噪声。与传统的岩性分类方法--高光谱角度制图法（SAM）相比,改进的算法能更精确地区分岩石相似光谱,识别易混淆岩性,对出现“异物同谱”现象的岩石也具有更好的区分能力。将SDEM、SAM方法应用于甘肃柳园地区TASI数据岩性分类研究中,可看出SDEM方法能识别出SAM未识别或识别错误的岩性。通过研究区野外查证,可知SDEM方法所得岩性分类结果更符合岩石实际分布情况。可见光谱离散能级波形匹配法具有较好的岩性分类效果,能更好地区分地物。     

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.     

集成多时相ETM+影像的证据推理湿地遥感分类

选择黑龙江省扎龙湿地自然保护区作为研究区,开展了基于Dempster-Shafer理论的证据推理方法(ER)湿地遥感空间分类研究,提出了一种针对ETM+多波段遥感影像的计算证据支持度的新算法,利用证据推理方法集成研究区5个时相的ETM+影像。研究表明,证据推理方法能有效集成多时相ETM+影像实现湿地空间分类,其总体分类精度比基于任一单时相影像的最大似然法(MLC)分类精度都高,提高幅度约为2%~12%。     

遥感技术在内蒙古东乌珠穆沁旗萨麦地区的找矿应用

本文以内蒙古东乌珠穆沁旗萨麦地区1:5万巴彦塔拉等4幅区域地质调查范围为研究区,以ETM+影像数据为信息源,以波谱理论为基础,从遥感图像中提取蚀变信息继而进行遥感找矿实践。针对区内铁染、羟基蚀变类型使用主成分分析等方法,将研究区划分为10个异常区,结合区域构造特征情况,对异常区域开展了1:1万路线调查,综合判定后,选择了4个找矿靶区进行了化探剖面探测并进行了成果分析,结果显示遥感蚀变信息与野外调查和化探异常吻合较好。     

庞西垌地区ETM+数据蚀变信息提取

以庞西垌地区为研究区,根据金属矿化蚀变岩的光谱特征,选取ETM+影像,采用主成分分析、波段比值、阈值分割等方法增强处理,提取矿化蚀变信息,结合研究区地质构造及成矿信息,圈定成矿远景区,为该区进一步找矿提供参考。     

Comparative analyses of East Texas forest cover maps generated from Landsat and AVHRR data

Comparing satellite data derived map products are affected by differences in data characteristics, image acquisition dates, processing techniques, and classification schemes used for assigning pixels to a thematic class. By comparing two forest maps generated from Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Very High Resolution Radiometer (AVHRR) images acquired on the same day, and processed using identical classification scheme and methods these differences were minimized. The ETM+ derived map had higher classification accuracy values and more precise area estimates than the AVHRR derived map. In the ETM+ derived map, 87 of the 599 verification data were misclassified, whereas in the AVHRR derived map, 155 of the 469 verification data were misclassified. Detailed error analyses by land cover class revealed that a land use based definition of forest accounted for 74% (64 out of 87) and 57% (89 out of 155) of the classification errors in ETM+ and AVHRR derived maps, respectively.     

多源遥感数据在新疆卡拉麦里地区岩矿识别中的应用

遥感技术广泛应用于地质基础调查、矿产资源勘探、环境评估和地质灾害调查等方面。它已从多光谱发展到高光谱阶段,Landsat- 8是目前最具有代表性和最常用的多光谱数据,ASTER具有高的分辨率和多波段特征,资源一号02D(ZY1- 02D)卫星是我国2019年发射的高光谱业务卫星。为了更好地了解多源遥感数据在岩矿识别中的作用,在新疆东天山卡拉麦里地区进行了相关研究。结果表明：Landsat- 8 OLI的PCA变换结果清晰识别了研究区不同的岩性和地层;使用Landsat- 8 OLI、ASTER和ZY1- 02D高光谱数据,分别采取不同的图像端元提取方法,在进行光谱分析的基础上,利用光谱角填图（SAM）即可得到研究区的主要矿物分类图件。通过野外验证,应用GIS技术进行集成和分析,修正相关图件后,便得到了精准的矿物分类综合图。研究表明：多源遥感数据的集成在岩矿识别方面效果良好、前景巨大。     

西准噶尔包古图Ⅴ号岩体围岩蚀变的特征及ETM+蚀变信息的提取

以新疆西准噶尔包古图Ⅴ号岩体为例,系统论述了包古图Ⅴ号含矿岩体的围岩蚀变分带和蚀变期次。结合ETM+数据的特征,选择多种遥感图像预处理方法组合,建立了基于典型蚀变矿物的特征光谱拟合技术的多光谱遥感蚀变信息提取模型,即遥感数据的归一化处理(Calibration )+掩膜(Mask)+混合像元分解(Endmember Unmixing)+波谱拟合(Spectral Feature Fitting)+ SAM+分类(分割)的CES模型。据此模型对岩体进行信息提取,并与化探资料叠加验证了该方法的可行性,取得了较满意的效果。     

Recovering the large gaps in Landsat 7 SLC-off imagery using weighted multiple linear regression (WMLR)

Since 2003, the permanent failure of the scan line corrector (SLC) of the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor has seriously limited the scientific applications and usability of ETM+ data. While a number of methods have been conducted to fill the regular un-scanned locations in ETM+ SLC-off images, only a few researches have been developed to recover the large gap areas in such images. In this study, an innovative gap filling method has been introduced to reconstruct the large gap locations in SLC-off images via multi-temporal auxiliary fill images. A correlation is established between the corresponding pixels in the target SLC-off image and two auxiliary fill images in parallel using the multiple linear regression (MLR) model in two successive steps. In the first step, almost half the gap locations have been recovered using the MLR model, then in the second step a weighted multiple linear regression (WMLR) algorithm is proposed to recover the remaining missing values. The simulated and actual case studies show that the proposed approach may provide a powerful tool for recovering the large gaps in SLC-off images, especially when there is a long time interval between the auxiliary fill images and the target SLC-off image.     

黑河中游绿洲灌溉区土地覆盖与种植结构空间格局遥感监测

以高空间分辨率、高光谱分辨率CASI航空遥感数据作为采样带,对黑河中游绿洲灌溉区土地覆盖和农作物种植结构空间格局进行遥感监测。设计了分层分类方法,综合采用基于像素和基于对象的2种遥感图像分类方法对航空样带区域进行土地覆盖制图。根据实地土地覆盖类型调查与目视解译,对样带土地覆盖和农作物种植结构的分类结果进行精度评价,总体分类精度为84.2%,Kappa系数为0.793。与样带区域2007年Landsat TM/ETM+土地覆盖产品相比,高分辨率CASI航空数据能够对树木、草地与农作物类别进行有效监测。监测结果表明,中游绿洲灌溉区内接近59.1%的地区为裸地与建筑用地;植被覆盖区域占39.8%,其中,农田34.9%,树木5.3%,草地仅有0.1%;而在农田区域中玉米为大宗作物,分类成数占96.1%。研究结果表明高质量与高分辨率的航空遥感数据能够实现对流域下垫面异质性进行有效监测,为生态—水文过程研究提供高分辨率的下垫面类型信息。     

Performance testing of selected automated coastline detection techniques applied on multispectral satellite imageries

Coastline detection has been of major interest for environmentalists and many methods have been introduced to detect coastline automatically. Remote Sensing techniques are the most promising ones to deliver a satisfactory result in this regard. In our study, the objective was to retrieve performance level of certain image processing techniques vigorously used for the purpose to delineate coastline automatically and they were tested against two images acquired almost on the same period by LISS III and LANDSAT ETM+ sensors. The algorithms used in the study are Water Index, NDVI, Complex Band Ratio, ISODATA, Thresholding, ISH Transfirmation techniques. Accuracy of the shoreline detection by classifying the image in land and water has been tried to be estimated in three ways, firstly with comparison to the visually interpreted high resolution google earth image, secondly field collected GCP data of reference points of classes and thirdly the raw image itself. But problem in temporal disparity caused the constraint doing accuracy assessment from the first two reference data and maps along the coast. As a whole although four techniques among six, show satisfactory results namely density slicing, ISODATA classification, Water Index and ISH transformation technique, in the case of LISS-III and ETM+, Water Index (with kappa value being 0.95 for LISS-III and 0.97 for ETM+) and Intensity-Hue-Saturation transformation techniques give better performance. Sensor to sensor variation might have introduced certain differences in shoreline detection in images of same season with similar tidal influence.