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新疆拜城地区煤田煤层自燃的陆地卫星遥感探测方法研究 总被引:1,自引:0,他引:1
利用TM图像,结合区域实测、地质和区域能源分布资料,分析了煤田煤层自燃的光谱特征,对煤田地火燃烧区进行定位;在此基础上对新疆拜城地区TM图像进行线性变换、边界增强、波段运算、多波段假彩色合成等增强处理,识别并提取影像中煤田煤层自燃引起的地表热信息、地表植被异常和岩石烧变信息等,通过分析达到探测煤田火区的目的。 相似文献
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利用卫星图像研究华北平原北西向隐伏活动断裂 总被引:3,自引:0,他引:3
本文主要简介华北平原地区北西向隐伏活动断裂在卫星图像上的显示特征,并结合断裂通过处地面水系、地球化学特征及钻孔地质资料等方面的证据。进一步论证了遥感图像指示的隐伏活动断裂的存在。 相似文献
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本文以实测的煤田火区地物波谱数据为依据,对用于煤田火区各地物解译的遥感信息源-TM图像的最佳时相选择,最佳波段组合煤田火区地物在TM图像上的影像特征进行了探讨。采用多时相TM图像对新疆奇台北山煤田火区进行动态监测及火情预测的成果进行了叙述,该勘查研究成果对指导该煤田火区灭火工程设计及后期防火管理的有较大实用价值。 相似文献
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本文通过基岩区航天飞机成像雷达(SIR-A)图像的解译,对影响成像雷达图像的地物几何形状(坡度、坡向)、表面粗糙度及地物物理电学特性等因素进行了分析研究,探讨了基岩区成像雷达图像地质解译的特点,利用SIR-A图像发现了在其它遥感图像上难以显示的川里环形(帚状)构造,结合区域成矿地质条件,对研究区内隐伏岩体、隐伏矿床作了预测。 相似文献
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本文通过基岩区航天飞机成像雷达(SIR-A)图像的解译,对影响成像雷达图像的地物几何 形状(坡度、坡向)、表面粗糙度及地物物理电学特性等因素进行了分析研究,探讨了基岩区 成像雷达图像地质解译的特点,利用 SIR-A图像发现了在其它遥感图像上难以显示的川里环 形(帚状)构造,结合区域成矿地质条件,对研究区内隐伏岩体、隐伏矿床作了预测。 相似文献
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遥感图像可以从宏观上反映活动断裂的空间展布规律和构造特征。在区域地质特征分析基础上,采用数据预处理、信息增强和数据融合等图像处理方法,提高了遥感图像的清晰度和可解译程度;根据遥感图像光谱特征和几何特征建立断裂构造带解译标志,进行断裂构造带及其活动性解译;结合野外调查,对麻城—团风断裂带进行了宏观分析和分段性活动的初步研究。研究结果表明:麻城—团风断裂带可按其控制力强弱分为北、中、南3段,北段图像线性特征明显,断裂解译标志显著;中段断裂控制力减弱,图像线性特征较模糊;南段为隐伏断裂。遥感技术在麻城—团风断裂带活动性调查中发挥了重要作用,特别是高分辨率遥感图像和遥感图像处理技术的应用不仅可以加快调查进度,还能为实地调查提供指导信息,从而显著提高调查效率与精度。 相似文献
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鄂尔多斯盆地是世界上罕见的特大型多时期复合含煤盆地,面积约30万km2,含有丰富的煤炭、石油及煤成气等矿产资源。盆地内主要含煤地层为晚古生界石炭系太原组、下二迭系山西组与中生界侏罗系延安组等地层。 1.技术方法 本文采用煤田遥感地质方法,选用不同比例尺卫星假彩色合成图像,通过选择典型区、波谱测量、图像增强处理、影像模式识别、地质构造解译、隐伏构造信息提取等工作,并对解译结果进行了重点验证,最后在分析盆地构造格局特征的基础上,运用煤成气地质理论对其赋存背景进行了分析。 2.盆地遥感地质构造格局及特征 解译结果表明,盆… 相似文献
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探讨了遥感多光谱与全色波段图像的融合问题,分析了基于IHS变换的小波包变换分解的遥感图像融合方法,提出了基于最优树分解的融合方法。此方法首先将多光谱图像进行IHS变换,然后对I分量和全色图像进行小波包分解和最优树分解,再进行融合,最后进行IHS 逆变换得到融合图像。此方法不仅得到较好的图像主观视觉效果,而且兼顾了客观上熵最大的原则。 相似文献
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Yangrong Ling Manfred Ehlers E. Lynn Usery Marguerite Madden 《ISPRS Journal of Photogrammetry and Remote Sensing》2007,61(6):381-392
Existing image fusion techniques such as the intensity–hue–saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. 相似文献
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近年来,随着遥感技术的迅猛发展,多源遥感影像数据越来越多,有效利用这些海量遥感数据是遥感领域的一大热门话题,同时,对融合后的遥感影像进行质量评价使融合处理过程得到优化,也是影像融合中必不可少的一个重要环节。重点利用ERDAS软件,分别采用Brovey变换法、IHS变换法、高通滤波法以及主成分分析法对影像进行融合实验,并对融合后的影像进行主观评价;采用Matlab编写程序,提取了融合影像的定量评价指标均值、标准差、平均梯度、信息熵和相关系数,完成了对融合影像的客观评价;最后对融合后的遥感影像进行了对比分析,得出主成分分析法的影像在光谱保持特性上最好,Brovey法在信息量的保持和清晰度上都优于其他的融合方法,而通过IHS变换法的融合影像与原始影像的相关性最好的结论。 相似文献
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Emerson Vieira Marcelino Antonio Roberto Formaggio Eduardo Eiji Maeda 《International Journal of Applied Earth Observation and Geoinformation》2009
The present work aims to assess the accuracy of six fusion techniques (Brovey, IHS, HSV, PCA, WTYO and WTVE) in order to compile landslide inventories using orbital images (ETM+ and PAN HRV). The study area is characterized by steep terrain and dense forest in Caraguatatuba, São Paulo State, Brazil. In terms of spatial quality, the Wavelet Transform technique provided the best results, presenting correlations above 90%. As for spectral quality, the best results were obtained with the IHS fusion. Based on the results, it may be concluded that the IHS is the best technique for preserving spatial and spectral information from the original images, so as to more clearly identify landslide scars. However, it was still not possible to typify the landslides from remote sensing data. Nonetheless, it is believed that image fusion techniques adequately met expectations in terms of their capacity to identify landslide for the creation of an inventory for the studied area. 相似文献
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We tested the effects of three fast pansharpening methods – Intensity-Hue-Saturation (IHS), Brovey Transform (BT), and Additive Wavelet Transform (AWT) – on sugarcane classification in a Landsat 8 image (bands 1–7), and proposed two ensemble pansharpening approaches (band stacking and band averaging) which combine the pixel-level information of multiple pansharpened images for classification. To test the proposed ensemble pansharpening approaches, we classified “sugarcane” and “other” land cover in the unsharpened Landsat multispectral image, the individual pansharpened images, and the band-stacked and band-averaged ensemble images using Support Vector Machines (SVM), and assessed the classification accuracy of each image. Of the individual pansharpened images, the AWT image achieved higher classification accuracy than the unsharpened image, while the IHS and BT images did not. The band-stacked ensemble images achieved higher classification accuracies than the unsharpened and individual pansharpened images, with the IHS-BT-AWT band-stacked image producing the most accurate classification result, followed by the IHS-BT band-stacked image. The ensemble images containing averaged pixel values from multiple pansharpened images achieved lower classification accuracies than the band-stacked ensemble images, but most still had higher accuracies than the unsharpened and individual pansharpened results. Our results indicate that ensemble pansharpening approaches have the potential to increase classification accuracy, at least for relatively simple classification tasks. Based on the results of the study, we recommend further investigation of ensemble pansharpening for image analysis (e.g. classification and regression tasks) in agricultural and non-agricultural environments. 相似文献
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High spatial resolution and spectral fidelity are basic standards for evaluating an image fusion algorithm. Numerous fusion methods for remote sensing images have been developed. Some of these methods are based on the intensity–hue–saturation (IHS) transform and the generalized IHS (GIHS), which may cause serious spectral distortion. Spectral distortion in the GIHS is proven to result from changes in saturation during fusion. Therefore, reducing such changes can achieve high spectral fidelity. A GIHS-based spectral preservation fusion method that can theoretically reduce spectral distortion is proposed in this study. The proposed algorithm consists of two steps. The first step is spectral modulation (SM), which uses the Gaussian function to extract spatial details and conduct SM of multispectral (MS) images. This method yields a desirable visual effect without requiring histogram matching between the panchromatic image and the intensity of the MS image. The second step uses the Gaussian convolution function to restore lost edge details during SM. The proposed method is proven effective and shown to provide better results compared with other GIHS-based methods. 相似文献