ASPRS

PE&RS January 2000

VOLUME 66, NUMBER 1
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING

Peer-Reviewed Article Abstracts

41 Radargrammetric Parameter Evaluation of an Airborne SAR Image
Joz Wu and De-Chen Lin

Abstract
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Digital synthetic aperture radar (SAR) images are composed of lines oriented along-track and pixels in a cross-track direction. Because of the motion of a SAR platform, the flight position and velocity parameters have time-dependent characteristics. Our objective consists in devising a model for the position/velocity parameters, then incorporating the model into radar-grammetric data processing. The interpolative parameter model is based on a linear prediction method with filtering.For a monoscopic airborne SAR image having a 12.0 km swath width and a 9.0 km along-track distance at an altitude of about 7.1 km, the positional root-mean-square errors are calculated using the ground coordinates available at 15 independent check points. Taking into account any model inadequacy, the errors inherent in the SAR  image forming, and the image point measurement errors, the position accuracy values amount to ±1.5, ±1.5 pixels horizontally, and ±1.2 pixels vertically.

49 Fusion of High Spatial and Spectral Resolution Images:  The ARSIS Concept and Its Implementation
Thierry Ranchin and Lucien Wald

Abstract
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In various applications of remote sensing, when high spatial resolution is required in addition with classification results, sensor fusion is a solution. From a set of images with different spatial and spectral resolutions, the aim is to synthesize images with the highest spatial resolution available in the set and with an appropriate spectral content. Several sensor fusion methods exist; most of them improve the spatial resolution but provide poor quality of the spectral content of the resulting image. Based on a multiresolution modeling of the information, the ARSIS concept (from its French name ``Amèlioration de la Rèsolution Spatiale par Injection de Structures'') was designed with the aim of improving the spatial resolution together with a high quality in the spectral content of the synthesized images. The general case for the application of this concept is described. A quantitative comparison of all presented methods is achieved for a SPOT  image. Another example of the fusion of SPOT XS (20-m) and KVR-1000 (2-m) images is given. Practical information for the implementation of the wavelet transform, the multiresolution analysis, and the ARSIS concept by practitioners is given with particular relevance to SPOT and Landsat imagery.

65 Airborne Laser Mapping of Assateague National Seashore Beach
W.B. Krabill, C.W. Wright, R.N. Swift, E.B. Frederick, S.S. Manizade, J.K. Yungel, C.F. Martin, J.G. Sonntag, Mark Duffy, William Hulslander, and John C. Brock

Abstract
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Results are presented from topographic surveys of the Assateague Island National Seashore using an airborne scanning laser altimeter and kinematic Global Positioning System (GPS) technology. The instrument used was the Airborne Topographic Mapper (ATM), developed by the NASA Arctic Ice Mapping (AIM) group from the Goddard Space Flight Center's Wallops Flight Facility. In November, 1995, and again in May, 1996, these topographic surveys were flown as a functionality check prior to conducting missions to measure the elevation of extensive sections of the Greenland Ice Sheet as part of NASA's Global Climate Change program. Differences between overlapping portions of both surveys are compared for quality control. An independent assessment of the accuracy of the ATM  survey is provided by comparison to surface surveys which were conducted using standard techniques. The goal of these projects is to make these measurements to an accuracy of ± 10 cm. Differences between the fall 1995 and 1996 surveys provides an assessment of net changes in the beach morphology over an annual cycle.

73 Multispectral Imagery Advanced Band Sharpening Study
Jim Vrabel

Abstract
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The goal of this project was to evaluate MSI band sharpening in four research areas. The first area explored the ``Effective Ground Sample Distance (GSD)'' and relative utility of multi-spectral imagery sharpened with panchromatic (pan) imagery. The second area examined interactions between data compression and the band sharpening process. The third area determined the effectiveness of band sharpening using a pair of high resolution sharpening bands covering different regions of the electromagnetic spectrum. The fourth area determined the effect of band sharpening on the accuracy of automated exploitation algorithms such as terrain categorization (TERCAT) and normalized difference vegetation index (NDVI). The results of this research show that the Effective GSD of the sharpened image can be predicted prior to fusion (an Effective GSD equation based on the GSDs of the multispectral and panchromatic input images is determined). The Effective GSD of the sharpened product is shown to be close to the GSD of the panchromatic sharpening band (94 percent of the possible GSD improvement is achieved). The research also showed that sharpened products demonstrate increased utility compared to the original low resolution MSI and the degree of increased utility for sharpened products can be predicted prior to fusion. The optimal sharpening algorithms based on this and prior research are also discussed.

81 Requirement of Ground Tie Points for InSAR DEM Generation
Guoqing Sun, K. Jon Ranson, Jack Bufton, and Michael Roth

Abstract
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Ground tie points have been used to improve the accuracy of a DEM  derived from interferometric SAR (InSAR) data. The number of tie points required for ensuring certain accuracy of the InSAR-derived DEM  was investigated in this study in two ways. One is the least-squares estimate of the corrections to a DEM using tie points, and the other is using an optimization procedure to estimate the uncertainties in estimations of InSAR parameters, mainly the baseline length, tilt angle, and reference phase using tie points, and resultant DEM error. It was found that, in terms of required tie points, both give comparable results. The latter method, though, can be applied in more realistic cases to design the tie point acquisition strategy for a mission.

87 Generating Viewsheds without Using Sightlines
Jianjun Wang, Gary J. Robinson, and Kevin White

Abstract
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A new simple algorithm for computing viewsheds using gridded digital elevation models (DEMs) is presented. By using reference planes rather than sightlines, considerable savings in computing time can be made. The time for computing a viewshed for every point of a DEM is constant, in contrast to with sightline-based algorithms in which the computing time varies with the location of a point in a DEM. The algorithm was tested by use of the DEMs of two areas. The viewshed of every point of both DEMs was calculated. The viewshed is, as might be expected, found to be strongly influenced by both relative and absolute position. Viewpoints at peaks and ridges have more visible area than the viewpoints at pits or bottom of valleys. However, the viewshed of the viewpoints at peaks or ridges with flat local ground surface, especially in plateau-like areas, could be less than the viewpoints in pits or bottom of valleys.

91 Matching Road Edges in Stereo-Image Sequences Using Data Association Techniques
Ayman F. Habib

Abstract
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Over the past decade, the need for digital land-related information grew tremendously to serve the needs of geographic information systems (GIS). Road network data are of special interest to GIS . Mobile mapping systems (MMS), which proved to be accurate and efficient data collection devices, can best capture these data. In this paper, road edges are detected and tracked in a sequence of image pairs. At successive image pairs, the system discerns the observations that are believed to originate from the features initialized in the first stereo pair. Data association algorithms offer the solution to this problem. The tracking procedure can be carried out for each target (road edge) independently using the Nearest-Neighbor Standard Algorithm (NNSA). Another approach is to perform the tracking by considering all targets and observations simultaneously using the Multiple Hypothesis Approach (MHA). The NNSA is being used in most photogrammetric applications that require feaÍture tracking in image sequences. The NNSA performs poorly when several targets compete for the same observation, especially when we deal with targets that are spatially close. On the other hand, this problem is accounted for in the MHA (which has been extensively used in feature tracking by robots equipped with radar). Data association techniques have the advantage of offering a statistical measure, which indicates the probability of the matching hypothesis being the right one. In this paper, tracking road edges in stereo-image sequences tested both the NNSA and the MHA. As expected, the MHA proved to be superior to the NNSA. The tracked road edges can be used to update the motion parameters of the system between the involved image pairs. Also, they can be used to autonomously navigate the MMS within the tracked road boundaries.
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