共查询到20条相似文献，搜索用时 28 毫秒
1.
It is well known that Landsat TM images are the most widely used remote sensing data in various fields. Usually, it has 7 different electromagnetic spectrum bands, among which the sixth one has much lower ground resolution compared with the other six bands. Nevertheless, it is useful in the study of rock spectrum reflection, geo-thermal resources exploration, etc. To improve the ground resolution of TM6 to the level as that of the other six bands is a problem. This paper presents an algorithm based on the combination of multi-variate regression model with semi-variogram function which can improve the ground resolution of TM6 by “fusing” the data of other six bands. It includes the following main steps: (1) testing the correlation between TM6 and one of TM1-5, 7. If the correlation coefficient between TM6 and another one is greater than a give threshold value, then select the band to the regression analysis as an argument. (2) calculating the size of the template window within which some parameters needed by the regression model will be calculated; (3) replacing the original pixel values of TM6 by those obtained by regression analysis; (4) using image entropy as a measurement to evaluate the quality of the fused image of TM6. The basic mechanism of the algorithm is discussed and the V C++ program for implemeting this algorithm is also presented. A simple application example is given in the last part of this paper, showing the effectiveness of the algorithm. 相似文献
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MA Hongchao LI Deren 《地球空间信息科学学报》2001,4(1)
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TM图像的光谱信息特征与最佳波段组合 总被引：2，自引：0，他引：2
本文分析了北自黑龙江省寒温带缓岗平原、南至广东省南亚热带丘陵等9个不同景观类型样区的TM图像数据,查明TM图像的光谱信息具3—4维结构,其物理含义相当于“亮度”、“绿度”和“热度”、“湿度”。在TM7个光谱图像中,一般以第5波段包含的地物信息最丰富。3个可见光波段(即第1,2,3波段)之间,两个中红外波段(即第5,7波段)之间相关性很高,表明这些波段的信息中有相当大的“重复性”或“冗余性”。第4,6波段则颇特殊,尤其是第4波段与各波段的相关性都很低,表明这个波段的信息有很大的独立性。计算20种组合的熵值的结果表明,由一个可见光波段、一个中红外波段及第4波段组合而成的彩色合成图像,一般具有最丰富的地物信息,其中又常以4,5,3或4,5,1波段的组合为最佳。 相似文献
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The leaf area index (LAI) of plant canopies is an important structural parameter that controls energy, water, and gas exchanges of plant ecosystems. Remote sensing techniques may offer an alternative for measuring and mapping forest LAI at a landscape scale. Given the characteristics of high spatial/spectral resolution of the WorldView-2 (WV2) sensor, it is of significance that the textural information extracted from WV2 multispectral (MS) bands will be first time used in estimating and mapping forest LAI. In this study, LAI mapping accuracies would be compared from (a) spatial resolutions between 2-m WV2 MS data and 30-m Landsat TM imagery, (b) the nature of variables between spectrum-based features and texture-based features, and (c) sensors between TM and WV2. Therefore spectral/textural features (SFs) were first selected and tested; then a canonical correlation analysis was performed with different data sets of SFs and LAI measurement; and finally linear regression models were used to predict and map forest LAI with canonical variables calculated from image data. The experimental results demonstrate that for estimating and mapping forest LAI, (i) using high resolution data (WV2) is better than using relatively low resolution data (TM); (ii) extracted from the same WV2 data, texture-based features have higher capability than that of spectrum-based features; (iii) a combination of spectrum-based features with texture-based features could lead to even higher accuracy of mapping forest LAI than their either one separately; and (iv) WV2 sensor outperforms TM sensor significantly. However, we need to address the possible overfitting phenomenon that might be brought in by using more input variables to develop models. In addition, the experimental results also indicate that the red-edge band in WV2 was the worst on estimating LAI among WV2 MS bands and the WV2 MS bands in the visible range had a much higher correlation with ground measured LAI than that red-edge and NIR bands did. 相似文献
6.
Aydın Kahriman Alkan Günlü Uzay Karahalil 《Journal of the Indian Society of Remote Sensing》2014,42(3):559-567
The objective of this study was to investigate the relationship between crown closure and tree density in mixed forest stands using Landsat Thematic Mapper (TM) reflectance values (TM 1- TM 5 and TM 7) and six vegetation indices (SR, DVI, SAVI, NDVI, TVI and NLI). In this study, multiple regression analysis was used to estimate the relationships between the crown closure and tree density (number of tree stems per hectare) using reflectance values and vegetation indices (VIs). The results demonstrated that the model that used SR and DVI had the best performances in terms of crown closure (R2?=?0.674) and the model that used the DVI and SAVI had the best performances in terms of tree density (R2?=?0.702). The regression model that used TM 1, TM 3 together with TM 4 showed the performances of the crown closure (R2?=?0.610) and the regression model that used TM 1 showed the performances of the tree density (0.613). Results obtained from this research show that vegetation indices (VIs) were a better predictor of crown closure and tree density than other TM bands. 相似文献
7.
Christopher Munyati 《国际地球制图》2013,28(3):11-22
Abstract The paper describes the use of Principal Component Analysis (PCA) of remote sensing images as a method of change detection for the Kafue Flats, an inland wetland system in southern Zambia. The wetland is under human and natural pressures but is also an important wildlife habitat. A combination of Landsat MSS and TM images were used. The images used were from 24 September 1984 (MSS), 3 September 1988 (MSS), 12 September 1991 (TM) and 20 September 1994 (TM). They were geometrically co‐registered and, in the process, the 80m resolution MSS images were resampled to 30m using nearest neighbour resampling. Preliminary PCA revealed that for the MSS images most of the data variance was in near infrared reflectance while for the TM images it was in mid and thermal infrared bands. Holding sensor type constant, separate inter‐band correlation analysis for each image could indicate whether the wetland was drier or wetter on one date versus another. The 1994 image was made the reference image and equivalent green, red and near infrared bands from the other images were radiometrically normalised with those on the reference image. All the bands, three from each date, were then merged into a twelve‐band image on which PCA for change detection was undertaken. A colour composite of eigen images from the resulting principal components was used in change detection. Hydrological data, indicating long‐term reduced inflow of water into the wetland due to human regulation, help explain some of the wetland change detected. Compared to a classification comparison approach to change detection for this area, PCA was found to be very useful in indicating where change had occurred, though interpretation of the changes was difficult without reference to the input images. The methodology appears to have potential use in habitat monitoring for this wetland area. 相似文献
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江苏近海岸水深遥感研究 总被引：8，自引：0，他引：8
以江苏近海辐射沙脊群海域为典型研究区,通过实测水深数据和水体光谱测量与分析,发现对应TM3和TM4波段的水体光谱反射率对水深信息敏感,线性相关系数分别达到-0.561和-0.694。结合多光谱遥感信息传输方程所推导出的水深信息对数反演模式,针对本研究区TM4和TM3波段数据所建立的水深预测模式的复相关系数R2为0.4793,对0-15m水深,预测水深和实测水深之间拟合较好。利用TM5波段反射率、出露沙洲反射率以及海水反射率的差异,通过建立掩膜图像,可较有效地对TM遥感图像进行水陆分离,提取TM图像中海水部分,进一步可通过常用的图像处理软件绘制每隔5m的TM水深遥感制图、等深线图。随着高空间、高光谱、高辐射分辨率遥感技术的发展,对浅海水域的水深和水下地形进行遥感探测的技术方法和应用将会不断地深入开展。 相似文献
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净初级生产力遥感估算模型空间尺度转换 总被引：2，自引：1，他引：2
采用基于混合像元的结构分析方法和支持向量机(SVM)算法,建立了高分辨率遥感数据(TM)向低分辨率遥感数据(MODIS)的尺度转换模型,实现了由高分辨率遥感数据获得的NPP向低分辨率遥感数据获得的NPP的空间尺度转换。对低分辨率遥感数据(MODIS)估算的NPP结果进行了尺度效应校正。结果表明:SVM回归模型模拟出的尺度效应校正因子Rj_corrected与1-F中覆盖度草地之间的相关性较高,R2达到0.81。尺度效应校正前的NPPMODIS与NPPTM的相关性较低,R2仅为0.69,RMSE为3.47;尺度效应校正后的NPPMODIS_corrected与NPPTM的相关性较高,R2达到0.84,RMSE为1.87。因此,经过尺度效应校正后的NPP无论是在相关性还是在误差方面有了很大程度的提高。 相似文献
11.
S. Rajendran A. Thirunavukkaraasu B. Poovalingaganesh K. Vinod Kumar G. Bhaskaran 《Journal of the Indian Society of Remote Sensing》2007,35(2):153-162
The remote sensing community in geology is widely using the Multispectral Landsat Thematic Mapper (TM) data which has a wider
choice of spectral bands (six between 0.45 and 2.35 μm, plus a thermal infrared channel 10.4-12.5 urn). These were evaluated for low-grade magnetite ores mapping over the high-grade
granulite region of Kanjamalai area of Tamil Nadu state, India. The Fourier Transform Infrared (FTIR) spectroscopy data (0.4-4.0
μm) for powders of the magnetite ores exposed with granulite rock and published spectral reflectance data were used as guides
in selecting TM band reflectance ratios, which maximize discrimination of magnetite ores on the basis of their respective
mineralogies. The study shows that the weathering mineralogy of magnetite ores causes absorption features in their reflectance
spectra which are particularly characteristic of the near infrared. Comparison of TM data with field and petrographic observations
shows the presence of magnetite and aluminosilicate minerals & show strong absorption at 0.7-1 μ.m wavelength spectral region
& increase in the product of two TM band ratios: band 5 (1.55-1.75 μm) to band 4 (0.76-0.9 μm) and band 3 (0.63-0.69 μm) to
band 4 (0.76-0.9 μm). Various computer image enhancement and data extraction techniques such as interactive digital image
classification techniques using color compositing stretched ratio, maximum likelihood and thresholding statistical approaches
using Landsat TM data are used to map the low-grade magnetite ores of the granulite region. The field traverses and local
verification enhanced to map the other rock types namely granulites and gneisses of the study area. 相似文献
12.
波段选择是高光谱遥感图像分类的重要前提，本文提出了一种用于高光谱遥感图像波段选择的改进二进制布谷鸟算法，通过使用混合二进制编码算法更新子代鸟巢和使用遗传算法交叉方式更新被发现鸟巢两个方面对二进制布谷鸟算法进行改进，找出在图像中起主要作用且相关性低的波段，实现对高光谱遥感图像降维。将本文算法运用于PaviaU数据集和AVIRIS数据集，并与二进制布谷鸟算法、二进制粒子群算法、最小冗余最大相关算法、Relief算法等进行对比分析。结果表明，改进二进制布谷鸟算法波段特征选择效率更高，且选取的波段更具代表性，能够较好地提高后续分类精度。 相似文献
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高分六号宽幅多光谱数据人工林类型分类 总被引：1，自引：0，他引：1
高分六号(GF-6)卫星于2018年成功发射,2019-03正式投入使用。由于GF-6宽幅相机的WFV(Wide Field of View)影像较GF-1的同类影像新增2个红边波段,将会提高对农业、林业、草原等资源监测能力。为了分析GF-6的WFV影像在人工林分类方面的能力,促进高分数据在林业领域的应用,本文选取广西高峰林场为研究区,以最新的GF-6 WFV影像为数据源,结合地面实测类型数据,进行广西南宁高峰林场的桉树,杉木等人工林类型提取。主要运用随机森林(random forests)的分层分类法:首先计算6种植被指数,并利用随机森林法进行植被指数的特征优选,然后确定4种波段组合数据集的分类方案,4种数据集分别为(1)无红边的前4个波段,(2)有红边的8个波段,(3) 8个波段加上未优化的植被指数特征组合,(4) 8个波段加上优化的植被指数特征组合。再进行WFV影像4种数据集的随机森林分类,随机森林采用分类回归树(CART)算法来生成分类树,结合了bagging和随机选择特征变量的优点,是一种有效的分类方法。最后比较4个方案的分类结果并进行精度验证。结果表明:方案2比方案1精度提高了4.99%,Kappa系数提高了0.058。说明包含红边的8波段数据比4个波段数据精度有大幅提升。方案4的8波段加上优化植被指数特征组合的分类精度最高,达到了85.38%,比方案2包含红边波段组和方案1无红边波段组的精度分别提高了3.98%,8.97%,Kappa系数分别提高了0.046,0.104。说明WFV影像加入红边波段比无红边波段精度明显增高。由结果可知,红边指数的引入,增强了植被信息,能够较准确地反映人工林类型特征差异,明显提升了人工林的分类精度。本研究方法可以有效改善广西人工林类型信息提取效果,为GF-6影像质量的评价及其在林业应用潜力提供科学参考依据。 相似文献
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基于多进制小波变换的遥感影像融合 总被引：7，自引：0，他引：7
首先介绍了遥感影像融合的理论和方法 ,然后在讨论多进制小波理论的基础上 ,提出了一种基于特征的多进制小波变换的影像融合算法 ,该算法根据待融合影像分辨率之比确定采用多进制小波 ,从而最大限度的利用了待融合影像的信息 ,防止影像信息的丢失。通过对具体影像的实验 ,证明融合后的影像最大限度地保留了待融合影像的光谱信息 ,同时提高了待融合影像的清晰度和空间分辨率。文中给出了SPOT全色影像与SPOT多光谱波段影像、SPOT全色影像与TM影像的融合结果 ,并与其他方法进行了比较 ,证明了本方法的优越性和自适应能力 相似文献
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在介绍遥感图像融合中IHS变换和小波包分析的基础上,提出了一种基于光谱特征保持的IHS变换与小波包分析相结合的图像融合算法。该方法可以最大限度地保留待融合图像的光谱信息,同时融合图像的清晰度和空间分辨率有了很大提高,图像纹理信息也得到了很好的保持。通过对SAR图像与Landsat(TM)多光谱图像的融合实验,证明了该方法的有效性。 相似文献
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天宫一号高光谱成像仪具有空间分辨率高、光谱分辨率高、图谱合一等特性，在中国航天高光谱领域具有里程碑的意义。针对一般遥感场景分类数据集尺度单一、光谱分辨率较低等问题，本文提出基于天宫一号的多谱段、高空间分辨率、多时相高光谱遥感场景分类数据集(TG1HRSSC)。利用天宫一号高光谱成像仪获取的高质量数据，经过辐射校正、几何校正、空间裁剪、波段筛选、数据质量分析与控制等，制作了一批通用的航天高光谱遥感场景分类数据集，通过载人航天空间应用数据推广服务平台（http://www.msadc.cn [2019-09-10]）进行分发和共享。该数据集包括天宫一号高光谱成像仪获取的城镇、农田、林地、养殖塘、荒漠、湖泊、河流、港口、机场等9个典型地物场景的204个高光谱影像数据，其中5 m分辨率全色谱段1个波段、10 m分辨率可见近红外谱段54个有效波段以及20 m分辨率短波红外谱段52个有效波段。研究利用AlexNet、VGG-VD-16、GoogLeNet等深度学习算法网络对构建的数据集进行场景分类的试验，结果表明该数据集的场景分类应用实现较好效果。由于该数据集具备高分辨、高光谱等特征优势，未来在语义理解、多目标检测等方面有着广泛的应用价值。 相似文献
18.
利用混合光谱分解与SVM估算不透水面覆盖率 总被引：1，自引：1，他引：0
对比了线性混合光谱分解模型(SMA)与支持向量机(SVM)在TM影像上估算不透水面覆盖率(ISP)的精度,通过SVM模型拟合TM像元光谱特征与样本ISP间的关联而获得对未知像元ISP的估算能力。对于天津市主城区的TM影像,选择学校区、工矿区和住宅区的高分辨率影像分类结果作为训练样本(7020个)和验证样本(1500个),SVM模型的ISP估算均方差(15.4%)优于SMA估算结果(19.4%);在增加缨帽变化“绿度分量”及混合光谱分解“高反射率分量”作为SVM特征变量后,ISP估算精度提高为12%。研究结果表明：SVM模型能够拟合各像元光谱组分间非线性关系且具有较好小样本泛化的性能,适用于地面样本较少的大区域ISP制图;增加与ISP相关性大的光谱特征向量作为SVM输入能提供更多的区域地物空间分布信息,能够调整无样本的地表类型的ISP估算值,提高区域ISP估算的整体精度。 相似文献
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Zeynab Ghanbari Mahmod R. Sahebi 《Journal of the Indian Society of Remote Sensing》2014,42(4):689-699
The intensity-hue-saturation method is used frequently in image fusion due to its efficiency and high spatial quality. The main shortage is its spectral distortion stemmed from replacement of intensity band with higher resolution image. In this study, a new method is introduced to improve the spectral quality of the Intensity-Hue-Saturation (IHS) algorithm. The goal of this study is to produce the fused image that has a better spectral and spatial quality with respect to the original images in term of visual comparison and the classification result. In this regard, an improved statistical approach is developed to combine an intensity band from IHS algorithm and an input high resolution image such as SAR or Panchromatic image. Then the intensity image is replaced by the combined image band. Final fused images are attained using the inverse IHS algorithm. The proposed fusion algorithm is tested on two data sets of: a) panchromatic and multi spectral bands of IKONOS image with the same acquisition date, and b) multi spectral and HH bands of IKONOS and TerraSAR-X images respectively with different acquisition dates. Moreover, the obtained results are compared with other fusion methods like IHS, Gungor, Brovey and synthetic variable ratio. The results show less spectral discrepancy of the proposed method comparing to other methods. Finally, the outcome of proposed method is classified and classification overall accuracy is improved by 5.6 and 2 percentage for data set ‘a’ and ‘b’ respectively. 相似文献