共查询到20条相似文献，搜索用时 500 毫秒
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Feizollah Masoumi Taymour Eslamkish Mehdi Honarmand Ali Akbar Abkar 《Journal of the Indian Society of Remote Sensing》2017,45(6):1039-1055
This study attempts to evaluate the capability of the advanced spaceborne thermal emission and reflection radiometer (ASTER) and the advantages of ground knowledge for generating maps portraying hydrothermally altered areas in relation to porphyry copper deposits. The northern part of the Rabor area in the Urumieh–Dokhtar magmatic belt, containing some copper mineralization occurrences, was investigated as a case study. Several image processing techniques, namely minimum noise fraction, pixel purity index, and n-dimensional visualization, contributed to the extraction of pure pixels as endmembers. The spectra of some rock samples collected around the well-known altered zones of the study area were resampled to ASTER bands and used to identify the image-extracted endmembers. Spectral analysis of the endmembers and ground sample spectra led to the identification of three types of hydrothermal alterations: (1) phyllic, (2) propylitic, and (3) argillic. The identified endmembers were used as the specified targets for mapping hydrothermal alteration zones over the study area by using a mixture tuned match filtering algorithm. Results demonstrate that high abundances within pixels correspond closely to the altered areas. Field observations, thin section, and X-ray diffraction of collected samples confirmed the accuracy of the alteration maps prepared by the application of the proposed methods. The final classified hydrothermal alteration maps showed the overall accuracy and kappa coefficient values of 85.41 and 0.72%, respectively. These results ascertain that ASTER data that use suitable image processing techniques appear consistent in mapping out the distribution of hydrothermally altered areas. In addition, ground knowledge data can act as a valuable information source to increase the image classification accuracy and reliability. 相似文献
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Kaveh Pazand Jamal Fereidoni Sarvestani M. Reza S. Ravasan 《Journal of the Indian Society of Remote Sensing》2013,41(2):379-389
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. 相似文献
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Virupakshagouda C. Patil Khalid A. Al-Gaadi ElKamil Tola Ahmed M. Zeyada Samy Marey 《国际地球制图》2018,33(1):70-88
To understand water productivity of crops cultivated in the Eastern Province of Saudi Arabia, this study was conducted to generate a reliable crop type map using a multi-temporal satellite data (ASTER, Landsat-8 and MODIS) and crop phenology. Classification And Regression Tree (CART) and ISO-DATA Cluster (IDC) classification techniques were utilized for the identification of crops. The Ideal Crop Spectral Curves were generated and utilized for the formulation of CART decision rules. For IDC, the stacked images of the phenology-integrated Normalized Difference Vegetation Index were utilized for the classification. The overall accuracy of the classified maps of CART was 76, 77 and 81% for ASTER, MODIS and Landsat-8, respectively. For IDC, the accuracy was determined at 67, 63 and 60% for ASTER, MODIS and Landsat-8, respectively. The developed decision rules can be efficiently used for mapping of crop types for the same agro-climatic region of the study area. 相似文献
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高光谱遥感积雪制图算法及验证 总被引：8，自引：0，他引：8
雪盖面积是高山地区和季节雪盖区水文和气象模型的重要输入因子。机载和星载遥感数据提取的雪盖面积是融雪径流模型的重要组成部分。对应不同传感器件的光谱特征，多种分类方法被相继提出。但是，缺乏相对独立的验证手段来评价各种分类方法，其主要原因是缺乏地面真实状态。针对该现状，本研究利用高光谱图像的细分光谱特征，建立高光谱影像及其对应“地面真相”的像对数据库来发展和验证积雪制图算法，并展示MODIS积雪制图算法验证和ASTER混合像元分解雪盖制图算法研究的应用实例。 相似文献
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There is considerable interest in optimizing geothermal exploration techniques via the mapping of alteration and evaporate mineralisation, as well as of thermal emissions associated with geothermally active areas on the Earth’s surface. Optical and thermal satellite sensor technologies, improvements in processing algorithms and the means for large scale (e.g. 1:250,000) spatial data distribution are required for detecting both these attributes. The extensive visible, -near, -shortwave and thermal infrared (VNIR-SWIR-TIR) data archive acquired by the multi-spectral Advanced Spaceborne Thermal Emission Reflectance Radiometer (ASTER) provides a rich source of geoscience related imagery for geothermal exploration. Examples of generating large scale mosaicked ASTER imagery to provide province to continental mineral mapping have been undertaken in areas including such as Australia, western USA, Namibia and Zagros Mountains Iran. In addition, ASTER’s thermal infrared imagery also provides night time land surface temperature (LST) estimates relevant for detecting possible geothermal related anomalies.This study outlines existing methods for the application of ASTER data for geothermal exploration in East Africa. The study area encompasses a section of the East African Rift System across the Tanzanian and Kenyan border. The area includes rugged volcanic terrain which has had geological mapping of limited coverage at detailed scales, from various heritages and mapping agencies. This study summarizes the technology, the processing methodology and initial results in applying ASTER imagery for such compositional and thermal anomaly mapping related to geothermal activity. Fields observations have been used from the geothermal springs of Lake Natron, Tanzania, and compared with ASTER derived spectral composition and land surface temperature results. Published geothermal fields within the Kenyan portion of the study area have also been incorporated into this study. 相似文献
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AbstractGeological mapping is one of the primary tasks of remote sensing. Remote sensing applications are especially useful when extreme environmental conditions inhibit direct survey such as in Antarctica. In this investigation, a satellite-based remote sensing approach was used for mapping alteration mineral zones and lithological units using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data in the Oscar II coast area, north-eastern Graham Land, Antarctic Peninsula. Specialized band ratios and band combinations were developed using visible and near infrared, shortwave infrared (SWIR) and thermal infrared spectral bands of ASTER for detecting alteration mineral assemblages and lithological units in Antarctic environments. Constrained Energy Minimization, Orthogonal Subspace Projection and Adaptive Coherence Estimator algorithms were tested to ASTER SWIR bands for detecting sub-pixels’ abundance of spectral features related to muscovite, kaolinite, illite, montmorillonite, epidote, chlorite and biotite. Results indicate valuable applicability of ASTER data for Antarctic geological mapping. 相似文献
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ASTER short-wave infrared bands were used to investigate the spectral discrimination of hydrothermally altered materials, based on the presence of minerals with diagnostic spectral features in wavelengths around 2200 nm (e.g. kaolinite and K-micas). Due to the presence of widespread albitized-greisenized materials, the Serra do Mendes granitoid, located in area of tropical savannah environment in Central Brazil, was selected for this study. The Spectral Angle Mapper (SAM) technique was used as an attempt to detect the presence of hydroxyl-bearing minerals in the domain of the hydrothermally altered materials. Results indicated that areas of altered materials were discriminated from the surrounding mainly due to the high overall reflectance of the whitish lithosols in these areas. The detection of hydroxyl-bearing minerals was blurred by the presence of a sparse grass cover in the alteration zone, which caused a slight increase in the SAM classification angles. As a consequence, the remote detection of hydroxyl-bearing minerals was restricted to a small number of pixels from barren areas. Results indicate that, for the environmental conditions of the study area, ASTER data are more efficacious for spectral characterization of rock–soil-vegetation associations than for the detection of alteration-derived minerals. 相似文献
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《International Journal of Digital Earth》2013,6(2):143-157
Abstract This study employs visible-near infrared and short wave infrared datasets of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to map salt diapirs and salt diapir-affected areas using Multi-Layer Perceptron (MLP) in the Zagros Folded Belt, Iran, and introduces the role of earth observation technology and a type of digital earth processing in lithological mapping and geo-environmental impact assessment. MLP neural network model with several learning rates between 0.01 and 0.1 was carried out on ASTER L1B data, and the results were compared using confusion matrices. The most appropriate classification image for L1B input to MLP was produced by learning rate of 0.01 with Kappa coefficient of 0.90 and overall accuracy of 92.54%. The MLP result of input data set mapped lithological units of salt diapirs and demonstrated affected areas at the southern and western parts of the Konarsiah and Jahani diapirs, respectively. Field observations and X-ray diffraction analyses of field samples confirmed the dominant mineral phases identified remotely. It is concluded that MLP is an efficient approach for mapping salt diapirs and salt-affected areas. 相似文献
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Hydrocarbon micro and macro seeps alter chemical and mineral composition of the Earth’s surface, providing prospects for detection with remote sensing tools. There have been several studies focusing on mapping these anomalies by utilizing ever evolving multispectral and hyperspectral imaging instruments, which has proven their capacity for mapping both hydrocarbons and hydrocarbon-induced alterations so far. These studies broadly comprise of methods like calculating band ratios, spectral angle mapping, spectral feature fitting, and principal component analysis as detection techniques. However, there is a lack of concentration on advanced signature based detection algorithms and unmixing methods for mapping surface manifestations of hydrocarbon microseeps. Signature based detection algorithms utilize target spectra to correlate with each pixel’s spectrum in order to allocate possible target locations. Unmixing methods, on the other hand, require no input spectra beforehand, aiming to resolve each pixel’s spectral constituents and their corresponding abundance fractions. In this paper, the potential of all these methods in mapping microseepage related anomalies are evaluated by implementing and comparing them for Gemrik Anticline, one of the prospective hydrocarbon exploration fields in Turkey. Hence, it provides a complete knowledge on determination surface manifestations of hydrocarbon microseeps with the help of well known supervised target detection algorithms and hyperspectral unmixing algorithms. The study area is located in the Southeastern Anatolia, between the cities of Adıyaman and Şanlıurfa. The spectral signatures were collected with Analytical Spectral Devices Inc. (ASD) spectrometer during the field studies conducted by Avcıoğlu (2010), to be utilized as an input to the signature based detection algorithms as well as a reference to select the related abundance map among the outputs of unmixing methods. Advanced Space Borne Thermal Emission and Radiometer (ASTER) image of the study region, with an atmospheric correction before running the algorithms, is selected for the applications. Among the applied algorithms, Simplex Identification via Split Augmented Lagrangian (SISAL) is selected as a base of comparison, as it possess minimum calculated error metrics in the experiments. Another unmixing method, the Minimum Volume Simplex Algorithm (MVSA), and signature-based techniques, Desired Target Detection and Classification Algorithm (DTDCA) & Spectral Matched Filter (SMF) follow the success of the SISAL, respectively. The Crosta technique, which is performed as a conventional approach for experimental comparisons, has also shown its capability, succeeding these algorithms. The study provides an overall assessment for methodologies to be used for hydrocarbon microseepage mapping, which also serves guidance for further exploration studies in the region. The potential of ASTER data for hydrocarbon-induced alterations is also emphasized as a cost effective tool for the future applications. 相似文献
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黄河口遥感图像光谱混合分解 总被引：6，自引：0，他引：6
探讨了用逻辑斯蒂法进行了光谱混合分解的新技术，采用黄河口LM图像进行了分析。结果表明，它不仅能给出分类结果图像，而且能产生组成像元各地类的丰度图像，说明分类图像是在某种置信度下的结果。 相似文献
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The characterization of fuel types is very important for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. However, due to the complex nature of fuel characteristic a fuel map is considered one of the most difficult thematic layers to build up. The advent of sensors with increased spatial resolution may improve the accuracy and reduce the cost of fuels mapping. The objective of this research is to evaluate the accuracy and utility of imagery from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery. In order to ascertain how well ASTER data can provide an exhaustive classification of fuel properties a sample area characterized by mixed vegetation covers was analysed. The selected sample areas has an extension at around 60 km2 and is located inside the Sila plateau in the Calabria Region (South of Italy). Fieldwork fuel type recognitions, performed before, after and during the acquisition of remote sensing ASTER data, were used as ground-truth dataset to assess the results obtained for the considered test area. The method comprised the following three steps: (I) adaptation of Prometheus fuel types for obtaining a standardization system useful for remotely sensed classification of fuel types and properties in the considered Mediterranean ecosystems; (II) model construction for the spectral characterization and mapping of fuel types based on a maximum likelihood (ML) classification algorithm; (III) accuracy assessment for the performance evaluation based on the comparison of ASTER-based results with ground-truth. Results from our analysis showed that the use ASTER data provided a valuable characterization and mapping of fuel types being that the achieved classification accuracy was higher than 90%. 相似文献
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In spite of the dominance of traditional mineral exploration methods that demand physical characterization of rocks and intense field work, remote sensing technologies have also evolved in the recent past to facilitate mineral exploration. In the present study, we have processed visible near infrared (VNIR) and shortwave infrared (SWIR) bands of Advanced space-borne thermal emission and reflection radiometer (ASTER) data to detect surface mineralization signatures in Mundiyawas - Khera area in Alwar basin, north-eastern Rajasthan, India using spectral angle mapper (SAM). The potential of SAM method to detect target under variable illumination condition was used to delineate galena, chalcopyrite, malachite etc. as surface signatures of mineralization. It was ensured that the identified surface anomalies were spectrally pure using pixel purity index. Spectral anomalies were validated in the field and also using X-Ray diffraction data. Spectral anomaly maps thus derived were integrated using weight of evidence method with the lineament density, geochemical anomaly, bouger anomaly maps to identify few additional potential areas of mineralization. This study thus establishes the importance of remote sensing in mineral exploration to zero in on potentially ore rich but unexplored zones. 相似文献
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运用K-L变换和NDBI(Normalized Difference Barren Index)指数法,对试验区--沧州市及其周边地区的ASTER遥感影像进行处理,然后分别对两种方法处理后的图像采用最小距离法监督分类,提取城市用地信息,并对分类后的图像进行对比,结果表明:NDBI指数法对城市用地信息提取的效果较好. 相似文献
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Mineral deposit mapping is very essential for sustainable and eco-friendly exploitation of natural resources. The Kingdom of Saudi Arabia has abundant natural resources such as natural gas, oil and minerals. It reserves high quantity of minerals such as phosphates, bauxites, copper, gold and other industrial minerals. The red soil regions located in Hail and Qassim provinces of Saudi Arabia have rich amount of bauxite (major aluminum ore) deposits. In order to initiate the focus on mapping of mineral deposits along this area, standardized hyper-spectral analysis has been carried out by using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data. The spectral signature of gibbsite (major element in bauxite) samples is analyzed with reference to the spectral features of gibbsite in the visible near infrared and short-wave infrared bands electromagnetic spectrum. Advanced hyper-spectral transformations such as minimum noise fraction function and pixel purity index have been performed to identify the target end-member. The existence of the mineral is confirmed by comparing the spectral signatures of the end-member with the predefined spectral plots of ASTER and United States Geological Survey spectral libraries. Finally, the end-members are mapped and their abundance is estimated in 0–1 scale. The study has opened up new areas for mapping of bauxite deposits in the area and leads to eco-friendly exploitation of natural resources. It also validates the high potential of ASTER multispectral satellite data for the exploration and mapping of mineral resources. 相似文献
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本文运用ASTER遥感数据识别与提取新疆南天山铜花山地区蛇绿混杂岩带岩性信息。首先,利用比值法快速区别岩性,并比较了识别同一种岩性的不同指数的性能;然后,将对数残差算法应用在ASTER数据的短波红外波段上,在区域尺度上把蛇绿岩杂岩体同围岩区分开来;最后,运用标准光谱数据和光谱角填图法识别出多种蛇绿岩成分及其空间分布。现有地质图和野外验证反映出该方法有一定效果。利用混淆矩阵对光谱角填图法分类结果定量评价,结果表明,把ASTER的可见光-近红外、短波红外波段数据结合在一起进行岩性分类,可以达到比单独用短波红外数据分类更高的分类精度。 相似文献
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This paper presents an application of Airborne Laser Scanning (ALS) data in conjunction with an IRS LISS-III image for mapping forest fuel types. For two study areas of 165 km2 and 487 km2 in Sicily (Italy), 16,761 plots of size 30-m × 30-m were distributed using a tessellation-based stratified sampling scheme. ALS metrics and spectral signatures from IRS extracted for each plot were used as predictors to classify forest fuel types observed and identified by photointerpretation and fieldwork. Following use of traditional parametric methods that produced unsatisfactory results, three non-parametric classification approaches were tested: (i) classification and regression tree (CART), (ii) the CART bagging method called Random Forests, and (iii) the CART bagging/boosting stochastic gradient boosting (SGB) approach. This contribution summarizes previous experiences using ALS data for estimating forest variables useful for fire management in general and for fuel type mapping, in particular. It summarizes characteristics of classification and regression trees, presents the pre-processing operation, the classification algorithms, and the achieved results. The results demonstrated superiority of the SGB method with overall accuracy of 84%. The most relevant ALS metric was canopy cover, defined as the percent of non-ground returns. Other relevant metrics included the spectral information from IRS and several other ALS metrics such as percentiles of the height distribution, the mean height of all returns, and the number of returns. 相似文献
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Bauxite deposits of Jharkhand in India are resulted from the lateritization process and therefore are often associated with the laterites. In the present study, ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer) image is processed to delineate bauxite rich pockets within the laterites. In this regard, spectral signatures of lateritic bauxite samples are analyzed in the laboratory with reference to the spectral features of gibbsite (main mineral constituent of bauxite) and goethite (main mineral constituent of laterite) in VNIR–SWIR (visible-near infrared and short wave infrared) electromagnetic domain. The analysis of spectral signatures of lateritic bauxite samples helps in understanding the differences in the spectral features of bauxites and laterites. Based on these differences; ASTER data based relative band depth and simple ratio images are derived for spatial mapping of the bauxites developed within the lateritic province. In order to integrate the complementary information of different index image, an index based principal component (IPC) image is derived to incorporate the correlative information of these indices to delineate bauxite rich pockets. The occurrences of bauxite rich pockets derived from density sliced IPC image are further delimited by the topographic controls as it has been observed that the major bauxite occurrences of the area are controlled by slope and altitude. In addition to above, IPC image is draped over the digital elevation model (DEM) to illustrate how bauxite rich pockets are distributed with reference to the topographic variability of the terrain. Bauxite rich pockets delineated in the IPC image are also validated based on the known mine occurrences and existing geological map of the bauxite. It is also conceptually validated based on the spectral similarity of the bauxite pixels delineated in the IPC image with the ASTER convolved laboratory spectra of bauxite samples. 相似文献