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Assessment and Evaluation of Band Ratios, Brovey and HSV Techniques for Lithologic Discrimination and Mapping Using Landsat ETM+ and SPOT-5 Data  [PDF]
Ahmed Madani
International Journal of Geosciences (IJG) , 2014, DOI: 10.4236/ijg.2014.51002

This study aims to assess and to evaluate band ratios, brovey and HSV (Hue-Saturation-Value) techniques for discrimination and mapping the basement rock units exposed at Wadi Bulghah area, Saudi Arabia using multispectral Landsat ETM+ and SPOT-5 panchromatic data. FieldSpec instrument is utilized to collect the spectral data of diorite, marble, gossan and volcanics, the main rock units exposed at the study area. Spectral profile of diorite exhibits very distinguished absorption features around 2.20 μm and 2.35 μm wavelength regions. These absorption features lead to lowering the band ratio values within the band-7 wavelength region. Diorite intrusions appear to have grey and dark grey image signatures on 7/3 and 7/2 band ratio images respectively. On the false color composite ratio image (7/3:R; 7/2:G and 5/2:B), diorite, marble, gossan and volcanics have very dark brown, dark blue, white and yellowish brown image signatures respectively. Image fusion between previously mentioned FCC ratio image and high spatial resolution (5 meters) SPOT-5 panchromatic image is carried out by using brovey and HSV transformation

Lithologic mapping using LANDSAT ETM+ and ASTER data

YU HaiKuo,LI PeiJun,

岩石学报 , 2010,
Abstract: The performance of lithologic mapping using both ASTER and LANDSAT ETM+ data was evaluated in this paper. Lithologic classifications using different spectral regions of ASTER data, different combination of them, and ETM+ data were performed respectively, especially using all ASTER and ETM+ bands. The results showed that different spectral regions of ASTER data produced different mapping accuracies. ASTER data obtained better performance in lithologic classification than that of using ETM+ data. Classification with all ASTER and ETM+ bands combined achieved high overall accuracy and Kappa coefficient, compared to those obtained with ASTER data or ETM+ data alone, which may indicate that both data provide complementary information for lithologic discrimination.
基于主成分分析与Brovey变换的ETM+影像植被信息提取  [PDF]
农业机械学报 , 2007,
Abstract: 在ETM+影像全色波段和多光谱数据融合时,Brovey变换是一种较好的融合方法,但是Brovey变换所利用的波段信息量少,并且在对融合后影像分类时常将存在阴影的植被覆盖区误判为水体。因此将主成分和归一化植被指数(NDVI)作为Brovey变换融合时的波段,实验结果显示融合后的影像更利于后期植被信息提取。
Study on Data Fusion and Classification of Landsat 7 ETM + Imagery
Landsat7 ETM+影像的融合和自动分类研究

XU Han-qiu,

遥感学报 , 2005,
Abstract: Fusion of images with different spatial resolution can improve visualization of the images involved. This study tries to show that the fusion of the images from the same sensor system can also improve classification accuracy of the images. Four image fusion algorithms have been employed in the study of data fusion and classification of Landsat 7 ETM imagery, taking southeastern part of Fuzhou City as the study area. These are the Smoothing Filter-Based Intensity Modulation (SFIM), Modified Brovey (MB) Transform, Multiplication (MLT) Transform, and High-Pass Filter (HPF) Transform. The effectiveness of the four fusion algorithms has been evaluated based on spectral fidelity, high spatial frequency information gain, and classification accuracy. The study reveals that the SFIM transform is the best method in retaining spectral information of original image, which does not cause spectral distortion, and achieving the highest classification accuracy. MB-fused image has highest spatial frequency information gain but significantly loses spectral properties of the original image. The study shows all four fusion algorithms used can significantly improve the classification accuracy of the fused imagery. Therefore, fused images from the same sensor system can be used for improving not only visual interpretation but also classification accuracy due to free of the seasonal difference, various solar illumination and other environmental condition differences, and co-registration errors, which are common to the fusion using images from different sensor systems.
基于Brovey融合与HSV锐化的ASTER影像绿地信息提取分析  [PDF]
地球信息科学学报 , 2009,
Abstract: 为了突出图像的边缘、线状目标或某些亮度变化率大的部分,生成边缘图像,运用Brovey融合和HSV锐化方法,对广州市部分地区的ASTER遥感影像进行处理,然后,对两种方法分别处理后的图像,采用平行六面体法监督分类,提取城市用地信息,并对分类后的图像进行对比试验,着重对城市绿地信息的提取进行分析,探究ASTER遥感数据的两种影像处理方法对城市绿地信息的提取效果,及其空间分布为城市生态评价和景观生态建设提供必要的基础数据。通过对比试验,结果显示Brovey方法较好地显示城市绿地的分布状况,可作为城市绿地动态监测的判别方法之一;融合后的影像能够清晰地显示研究区城市绿地的分布结构及毗邻关系;通过采用区域放大、勾画不同地类边缘轮廓、配合人工解译等工作,能够增加城市绿地与其他用地类型的差异,突显城市绿地的分布、结构、生态学特征。
Rice Yield Estimation Using Landsat ETM+ Data and Field Observation  [cached]
I Wayan Nuarsa,Fumihiko Nishio,Chiharu Hongo
Journal of Agricultural Science , 2012, DOI: 10.5539/jas.v4n3p45
Abstract: Forecasting rice yield before harvest time is important to supporting planners and decision makers to predict the amount of rice that should be imported or exported and to enable governments to put in place strategic contingency plans for the redistribution of food during times of famine. This study used the Normalized Difference Vegetation Index (NDVI) of Landsat Enhanced Thematic Mapper plus (ETM+) images of rice plants to estimate rice yield based on field observation. The result showed that the rice yield could be estimated using the exponential equation of y = 0.3419e4.1587x, where y and x are rice yield and NDVI, respectively. The R2 and SE of the estimation were 0.852 and 0.077 ton/ha, respectively. An accuracy assessment of rice yield estimation using Landsat images was performed by comparing the rice yields from the estimation result and the reference data. The results show that the linear relationship with the R2 and SE of the estimation were 0.9262 and 0.21 ton/ha, respectively. The R2 is greater than or equal to 0.8, which demonstrates a strong agreement between the remotely sensed estimation and the reference data. Thus, the Landsat ETM+ has good potential for application to rice yield estimation.
Object-oriented classification of Landsat ETM+ satellite image
Stanis aw Lewiński
Journal of Water and Land Development , 2006, DOI: 10.2478/v10025-007-0008-4
Abstract: This paper presents results of object-oriented classification of Landsat ETM+ satellite image conducted using eCognition software. The classified image was acquired on 7 May 2000. In this particular study, an area of 423 km2 within the borders of Legionowo Community near Warsaw is considered. Prior to classification, segmentation of the Landsat ETM+ image is performed using panchromatic channel, fused multispectral and panchromatic data. The applied methods of classification enabled the identification of 18 land cover and land use classes. After the classification, generalization and raster to vector conversion, verification and accuracy assessment are performed by means of visual interpretation. Overall accuracy of the classification reached 94.6%. The verification and classification results are combined to form the final database. This is followed by comparing the object-oriented with traditional pixel-based classification. The latter is performed using the so-called hybrid classification based on both supervised and unsupervised classification approaches. The traditional pixel-based approach identified only 8 classes. Comparison of the pixel-based classification with the database obtained using the object-oriented approach revealed that the former reached 72% and 61% accuracy, according to the applied method.
Mangrove Forests Mapping in the Southern Part of Japan Using Landsat ETM+ with DEM  [PDF]
Bayan Alsaaideh, Ahmad Al-Hanbali, Ryutaro Tateishi, Toshiyuki Kobayashi, Nguyen Thanh Hoan
Journal of Geographic Information System (JGIS) , 2013, DOI: 10.4236/jgis.2013.54035

A regional map of mangrove forests was produced for six islands located in the southern part of Japan by integrating the spectral analyses of Landsat Enhanced Thematic Mapper plus (ETM+) images with a digital elevation model (DEM). Several attempts were applied to propose a reliable method, which can be used to map the distribution of mangrove forests at a regional scale. The methodology used in this study comprised of obtaining the difference between Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI), band ratio 5/4, and band 5, from Landsat ETM+, and integrating them with the topographic information. The integration of spectral analyses with topographic data has clearly separated the mangrove forests from other vegetation. An accuracy assessment was carried out in order to check the accuracy of the results. High overall accuracy ranging from 89.3% to 93.6% was achieved, which increased the opportunity to use this methodology in other countries rich in mangrove forests.

Comparison on Urban NDVI from Landsat ETM and QUICKBIRD Data

YANG Pei-yu,CHEN Sheng-bo,WU Qiong,LV Le-ting,LI Ming-jun,

遥感技术与应用 , 2008,
Abstract: This report assesses the effectiveness of different resolutions for estimations on vegetation cover in urban area using Landsat-7 ETM+ and Quickbird data.The Normalized Difference Vegetation Index (NDVI) data are first generated from these two types of data in Beijing area.It shows that a finer imagery can distinguish a smaller areas,thus Quickbird image is better for the urban area.However,for a larger area or a homogenous vegetation cover,these is little difference.Landsat ETM image is more appropriate for a larger area due to its lower cost and more bands when compared with the Quickbird imge.
Evaluation and Analysis on Image Fusion of ETM

YU Jun-ming,ZHOU Yi,WANG Shi-xin,WANG Li-tao,
,王世新,王丽涛 

遥感技术与应用 , 2007,
Abstract: In this paper,five image fusion algorithms including HIS transformation,Brovey transformation,Weighting fusion,SFIM transformation and ISVR transformation are experimented between Landsat-7 ETM PAN band and multi-spectral bands.The result of different fusion methods is evaluated qualitatively and quantitatively by comparing the spectral fidelity and the spatial resolution.The study indicates that HIS transformation distorts the spectral quality most seriously.Brovey transformation is not very nice both in retaining the spectral quality and improving the spatial resolution.The result of Weighting fusion depends on the weighting seriously.Smoothing Filter-Based Intensity Modulation(SFIM) distorts the spectral quality greatly,however,it can not improve the spatial resolution.Improved Synthetic Variable Ratio(ISVR) is very fit for fusion with ETM images on the who1e.ISVR technique distorts the spectral quality slightly,as well as improves the spatial resolution obviously.The advantage is that it considers the relation of panchromatic band and multispectral bands,which is ignored by other methods in this paper.
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