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3rd International Conference on Information Fusion, FUSION 2000

作者： Mostafa, Mostafa G. Farag, Aly A. Essock, Edward Computer Vision and Image Processing Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY 40292 United States Department of Psychology University of Louisville Louisville KY 40292 United States

ISBN: (纸本)2725700000

Multi-modality image registration and fusion are essential steps in building 3D models from remote sensing data. In this paper, we present a neural network technique for the registration and fusion of multi-modality remote sensing data for the reconstruction of 3D models of terrain regions. A feedforward neural network is used to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data are presented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusion results. © 2000 Int. Soc. Inf. Fusion.

关键词： image fusion

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A linear mixture analysis-based compression for hyperspectral image analysis

A linear mixture analysis-based compression for hyperspectra...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： Q. Du Chein-I Chang D.C. Heinz M.L.G. Althouse I.W. Ginsberg Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA Department of Energy Remote Sensing Laboratories Las Vegas NV USA

The authors present a fully constrained least squares linear spectral mixture analysis-based compression technique for hyperspectral image analysis, particularly, target detection and classification. Unlike most compression techniques that directly deal with image gray levels, the proposed compression approach generates the abundance fractional images of potential targets present in an image scene and then encodes these fractional images so as to achieve data compression. Since the vital information used for image analysis is generally preserved and retained in the abundance fractional images, the loss of information may have very little impact on image analysis. In some occasions, it even improves analysis performance. AVIRIS data experiments demonstrate that it can effectively detect and classify targets while achieving very high compression ratios.

关键词： image analysis image coding Hyperspectral imaging Hyperspectral sensors Layout Object detection Spectral analysis Performance analysis Feature extraction Pixel

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Unsupervised hyperspectral image analysis using independent component analysis

Unsupervised hyperspectral image analysis using independent ...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： Shao-Shan Chiang Chein-I Chang I.W. Ginsberg Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA Department of Energy Remote Sensing Laboratories Las Vegas NV USA

In this paper, an ICA-based approach is proposed for hyperspectral image analysis. It can be viewed as a random version of the commonly used linear spectral mixture analysis, in which the abundance fractions in a linear mixture model are considered to be unknown independent signal sources. It does not require the full rank of the separating matrix or orthogonality as most ICA methods do. More importantly, the learning algorithm is designed based on the independency of the material abundance vector rather than the independency of the separating matrix generally used to constrain the standard ICA. As a result, the learning algorithm is able to converge to non-orthogonal independent components. This is particularly useful in hyperspectral image analysis since many materials extracted from a hyperspectral image may have similar spectral signatures and may not be orthogonal. The AVIRIS experiments have demonstrated that the proposed ICA provides an effective unsupervised technique for hyperspectral image classification.

关键词： Hyperspectral imaging image analysis Independent component analysis Hyperspectral sensors Principal component analysis Vectors Laboratories Spectral analysis Pixel Composite materials

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SeaWinds on QuikScat radiometric measurements and calibration

SeaWinds on QuikScat radiometric measurements and calibratio...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： W.L. Jones R. Mehershahi J. Zec D.G. Long UCF-Electrical and Computer Engineering Department Central Florida Remote Sensing Laboratory Orlando FL USA BYU Center for Remote Sensing BYU Department of Electrical and Computer Engineering Microwave Earth Remote Sensing Laboratory Provo UT USA

Originally designed as a radar scatterometer, SeaWinds measurements have recently been expanded to include brightness temperature of the Earth. Not since 1972, when the S-193 RADSCAT flew on NASA's SkyLab, has such a combined active/passive microwave remote sensor in flown in space. Now, with the launch of the SeaWinds on the QuikScat satellite in June of 1999, simultaneous, active/passive measurements are again available for Earth remote sensing. This technological advance is the result of several changes in the SeaWinds instrument configuration compared to previous satellite scatterometers (SeaSat, ERS-1 and -2 and NSCAT). Foremost, SeaWinds uses conical scanning "pencil" beams to simultaneously measure both the surface backscatter and microwave emission. In this paper we describe the radiometric processing and calibration that enables the surface brightness temperature measurement.

关键词： Calibration Radar measurements Spaceborne radar Microwave radiometry Brightness temperature Earth Passive microwave remote sensing Space technology Satellite broadcasting Radar remote sensing

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SeaWinds beam and slice balance using data over Amazonian rainforest

SeaWinds beam and slice balance using data over Amazonian ra...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： J. Zec W.L. Jones D.G. Long UCF-Electrical and Computer Engineering Department Central Florida Remote Sensing Laboratory Orlando FL USA BYU Department of Electrical and Computer Engineering Utah

The primary application of a scatterometer is estimation of wind vectors over the sea surface, but a variety of other geophysical parameters can be retrieved as well. To eliminate ambiguity in retrieved wind direction, multiple looks are required at the observed area. These looks are provided by multiple scatterometer antenna beams. To achieve the desired accuracy of wind vectors and other retrieved geophysical products, the antenna beams must be calibrated to within /spl plusmn/0.2 dB. Pre-launch calibration alone is insufficient for such a level of beam balance. Postlaunch calibration/validation activities are therefore required for scatterometer missions. This paper describes beam balance procedure applied following the recent launch of the SeaWinds scatterometer on the QuikScat spacecraft. This work was similar to the NSCAT post-launch verification. A brief description is given of the SeaWinds instrument. A calibration data set is introduced. An azimuth beam balance and a comparison with preceding NSCAT instrument is presented. High-resolution slice-balance results are also shown.

关键词： Radar measurements Spaceborne radar Calibration Instruments Radar cross section Radar antennas Polarization Signal resolution Signal processing Satellites

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A dual polarization multi-frequency microwave radiometer

A dual polarization multi-frequency microwave radiometer

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： E.J. Knapp J.R. Carswell C.T. Swift Department of Electrical & Computer Engineering Microwave Remote Sensing Laboratory University of Massachusetts Amherst MA USA

The University of Massachusetts (UMASS) Microwave remote sensing laboratory (MIRSL), funded under the U.S. department of Agriculture (USDA), has designed and fielded a dual polarization C band microwave radiometer operating at six frequencies from 4.6 to 7.1 GHz. The Simultaneous Frequency Microwave Radiometer (SFMR2) provides continuous radiometric measurements at all six frequencies as well as providing dual polarization capability. The SFMR2 participated in two field campaigns in the summer/fall of 1999. The first experiment was the USDA sponsored Southern Great Plains 1999 soil moisture campaign on board the NCAR C-130. The second was during Hurricane Research/Reconnaissance flights on board the NOAA P3 aircraft. Brightness temperature data as well as wind speed and rain rate estimates derived from SFMR2 data from the hurricane flights are presented.

关键词： Polarization Microwave radiometry US department of Agriculture Hurricanes remote sensing Laboratories Microwave measurements Frequency measurement Soil measurements Soil moisture

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Validation of QuikScat radiometric estimates of rain rate

Validation of QuikScat radiometric estimates of rain rate

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： W. Linwood Jones M. Susanj J. Zec Jun-Dong Park UCF-Electrical and Computer Engineering Department Central Florida Remote Sensing Laboratory Orlando FL USA

The SeaWinds scatterometer on the QuikScat satellite simultaneously measures the active (scattering) and passive (emission) microwave characteristics of the Earth's surface. This paper describes the use of the QuikScat Radiometer (QRad) brightness temperature measurements to infer rain rate over the oceans. A discussion of the rain rate algorithm is presented, and comparisons are made with near-simultaneous integrated rain rate measurements from the Tropical Rainfall Measuring Mission (TRMM) Microwave imager (TMI). These results demonstrate the potential for using QRad rain index to infer moderate to high rain rates over the ocean.

关键词： Rain Sea measurements Microwave measurements Microwave radiometry Oceans Radar measurements Satellite broadcasting Scattering Earth Sea surface

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Biophysical and spectral characteristics of cool- and warm-season grasslands under three land management practices in Eastern Kansas

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Natural Resources Research 2000年第4期9卷 321-331页

作者： Guo, Xulin Price, Kevin P. Stiles, James M. Kansas Applied Remote Sensing Program (KARS) Department of Geography University of Kansas Lawrence KS 66045 2335 Irving Hill Road United States Radar Systems and Remote Sensing Laboratory (RSL) Department of Electrical Engineering and Computer Science University of Kansas Lawrence KS 66045 2335 Irving Hill Road United States Lawrence KS 66045 2335 Irving Hill Road United States

Grasslands are the largest of the Earth's four major vegetation types and are among the most agriculturally productive lands. Grassland management practices alter biophysical factors, such as plant species composition, soil structure and chemistry, and primary productivity. Large-scale changes in land management practices can have significant impacts on available natural resources, therefore impacting a regional socioeconomics. For these reasons, an improved understanding of the geographic distribution of changing land management practices and how these changes affect grassland biophysical characteristics of an area is critical to improve land use planning and practices. This study investigated the spectral characteristics, as measured using satellite remotely sensed data, of three land management practices [grazing, haying, and management under Conservation Reserve Program (CRP)] on areas dominated by cool- and warm-season grasslands. The satellite imagery was acquired in May, July, and September in 1997 over Douglas County, Kansas. Biomass, vegetation cover, and species richness data were collected around the satellite overflight periods. Our results indicate that the biophysical characteristics and spectral reflectances are significantly different among the three management practices over cool- and warm-season grasslands. Interestingly, sites grazed by livestock had the highest species richness and the highest forb cover, although the total cover is almost the same as the other practices, and they have the highest near-infrared reflectance throughout the growing season. © 2000 International Association for Mathematical Geology.

关键词： Landsat Tallgrass prairie Thematic Mapper (TM)

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Scatterometer-retrieved hurricane wind direction ambiguity removal using spiral dealias

Scatterometer-retrieved hurricane wind direction ambiguity r...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： J. Zec W.L. Jones UCF-Electrical and Computer Engineering Department Central Florida Remote Sensing Laboratory Orlando FL USA

A notable shortcoming of scatterometry of high wind speeds is the apparent under estimation of the speed of the winds, but wind direction errors are also important. For the direction, a major source of error is associated with difficulty in selecting the proper wind direction from multiple possible solutions known as aliases. The wind retrieval process is based on a relation between wind-induced sea surface roughness and /spl sigma//sup 0/. This relation, denoted as geophysical model function (GMF), is semiempirically derived from collocated sets of radar /spl sigma//sup 0/ measurements and in-situ wind condition observations. Unfortunately, the bi-harmonic nature of the /spl sigma//sup 0/ anisotropy with wind direction results in multiple wind vectors solutions (speed and directions combinations) from a collocated set of scatterometer measurements. Both /spl sigma//sup 0/ measurement noise and a weak GMF wind direction signature contribute to ambiguity in the retrieved wind. In most wind retrieval algorithms, ambiguity in direction is a major component of the direction error. This paper investigates a simple method aimed at improving ambiguity removal during wind retrievals in tropical cyclones. The method uses the a priori knowledge of the general wind circulation about the center of rotation (eye) to produce a spiral "de-alias" of directions in multiple wind solutions. Technique is illustrated using observations from the SeaWinds instrument on board the QuikScat satellite.

关键词： Radar measurements Hurricanes Wind speed Geophysical measurements Sea measurements Sea surface roughness Spaceborne radar Anisotropic magnetoresistance Velocity measurement Noise measurement

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Application of generalized constrained energy minimization approach to urban road detection

Application of generalized constrained energy minimization a...

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IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： Chinsu Lin Chuin-Mu Wang Chein-I Chang Environmental Monitoring and Planning Laboratory Department of Forestry National Chiayi University Chiayi Taiwan Department of Electrical Engineering National Cheng Kung University Tainan Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County MD USA

Classification of thematic layers have been used to update digital databases, particularly digital maps which can be accessed on the Internet by a fast growing number of users. One of the most important features in digital maps is traffic patterns and road networks. Unfortunately, due to low spectral and spatial resolutions of satellite imagery, many roads cannot be extracted at pixel level since the width of most urban and rural roads is less than the pixel size. In addition, road spectral signatures vary from pixel by pixel due to natural background. In this paper, an approach combining a subpixel detection method, called generalized constrained energy minimization with a principal component analysis-based fusion technique is proposed for urban road extraction. Experimental results show that the proposed method can effectively detect roads in Landsat TM and SPOT panchromatic images.

关键词： Roads Satellites Pixel image databases Spatial databases Internet Telecommunication traffic Spatial resolution Minimization methods remote sensing

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