ASPRS

PE&RS March 2000

VOLUME 66, NUMBER 3
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING

Peer-Reviewed Article Abstracts

281 Exploring Ground Truth from Given Photos by Applying a Model-Based Approach
Yishuo Huang and Bon A. Dewitt

Abstract
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Virtual reality is increasingly viewed as a cost-effective alternative for training, as well as capable of providing advanced activities such as mission preview, planning, and rehearsal. Of particular interest is the ability to explore ground truth utilizing photo databases or satellite imagery created by remote sensing. Ensuring the success of remote-sensing-based virtual reality depends on a system's ability to reconstruct a 3D  scene in object space with a realistic appearance. To accomplish this task, this study presents a novel system with the following characteristics: (1) image registration, (2) feature correspondence and construction, as well as (3) realistic 3D  scene feature rendering. Image registration is achieved by employing a method based on the high-dimension concept. To obtain a high speed, feature correspondence is implemented using an edge-based method in a multiresolution scheme. Rendered results in this study demonstrate the feasibility of the proposed system.

287 Generation of Hierarchical Multiresolution Terrain Databases Using Wavelet Filtering
Donald E. McArthur, Robert W. Fuentes, and Venkat Devaragan

Abstract
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An approach for generating a hierarchical, multiresolution polygonal database from raw elevation data using the wavelet transform is described. We first present experimental results in the use of the wavelet transform to produce filtered data that progress from coarse to fine resolution in a tunable manner. These initial conclusions logically lead to our proposed enhancement method. In this approach, we utilize wavelet filtered data in conjunction with a hierarchical triangulation technique to create a set of increasing resolution models. This methodology utilizes a tunable filtering scheme to retain the dominant terrain features at each level and, more importantly, to maintain a database hierarchy. This procedure was implemented with real elevation data, and the results that we present are the relationship between the number of triangles created and the root-mean-squared errors of the triangular models along with 2D  and 3D  plots of the resultant triangulations.

297 Application of DEM Data to Landsat Image Classification:  Evaluation in a Tropical  Wet-Dry Landscape of Thailand
Apisit Eiumnoh and Rajendra P. Shrestha

Abstract
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Integration of ancillary data in digital image classification has been shown to improve land-use/land-cover discrimination and classification accuracy. Studies demonstrating such techniques in the context of the tropical landscape are lacking. Cloud related problems limiting data acquisition during the crop season are frequently encountered in the humid tropics. Generally, cloud-free data are obtained during the dry season. The reason for carrying out this study was to explore and evaluate the use of ancillary data, such as elevation, in Landsat thematic mapper classification to produce a land-use/land-cover map of the Sakae Krang watershed of Thailand. Altogether, 12 feature sets containing the TM  original bands, ratios, normalized differential vegetation index, principal components, and a digital elevation model were tested using unsupervised ISODATA  clustering. Incorporation of elevation data was found to improve land-cover discrimination with relatively higher classification accuracy (77.5 percent) compared to TM data alone (65.3 percent). Further improvement in the classification accuracy (84.3 percent) was obtained when using elevation data under a supervised technique. The study also indicated that the classification results can be further improved by incorporating other geomorphometric variables, such as slope and soil moisture regime.

305 Integrating Spectral, Spatial, and Terrain Variables for Forest Ecosystem Classification
Paul Treitz and Philip Howarth

Abstract
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Sets of spectral, spectral-spatial, textural, and geomorphometric variables derived from high spatial resolution Compact Airborne Spectrographic Imager (CASI) and elevation data are tested to determine their ability to discriminate landscape-scale forest ecosystem classes for a study area in northern Ontario, Canada. First, linear discriminant analysis for various spectral and spectral-spatial variables indicated that a spatial resolution of approximately 6 m was optimal for discriminating six landscape-scale forest ecosystem classes. Second, texture features, using second-order spatial statistics, significantly improved discrimination of the classes over the original reflectance data. Finally, addition of terrain descriptors improved discrimination of the six forest ecosystem classes. It has been demonstrated that, in a low to moderate relief boreal environment, addition of textural and terrain variables to high-resolution CASI reflectance data provides improved discrimination of forest ecosystem classes.

319 Using High Spatial Resolution Multispectral Data to Classify Corn and Soybean Crops
Gabriel B. Senay, John G. Lyon, Andy D. Ward, and Sue E. Nokes

Abstract
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Digital images of a corn and soybean site in Ohio were acquired several times during the growing season using a multispectral scanner mounted on an aircraft. The goal of this study was to evaluate the use of this high spatial resolution (1-m) data toidentify corn and soybean crops at various growth stages. Maximum distinction between corn and soybeans was achieved using the near-infrared bands when the crops were mature, while the visible bands were more useful when the soybeans were senescing. Spectral class differences were related to leaf nitrogen, soil water content, soil organic matter, and plant biomass. An approach is presented for identifying corn and soybeans crops where little or no reference data are available. The approach is based on the red and near-infrared bands and using the Simple Vegetation Index or the Normalized Difference Vegetation Index.

329 Application of Multispectral Imagery to Assessment of a Hydrodynamic Simulation of an Effluent Stream Entering the Clinch River
Alfred J. Garrett, John M. Irvine, Amy D. King,  Thomas K. Evers, Daniel A. Levine, Clell Ford, and  John L. Smyre

Abstract
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This study investigates the feasibility of using remote sensing systems to estimate and model contaminant transport at known hazardous waste sites. We used airborne (Daedalus) imagery and 3D hydrodynamic simulations to estimate the flow rate of Poplar Creek as it enters the Clinch River, located on the U.S. Department of Energy (DOE) Oak Ridge Reservation (ORR) in Tennessee. The collection of ground-truth data and the simulations were complicated by the variability of the Clinch River flow, which we attempted to reproduce in the simulations. Comparisons of the Daedalus imagery to images created from the simulations led to the conclusion that the Clinch River/Poplar Creek system shifts back and forth between three distinct flow regimes that have different pollutant transport patterns. Results of this research suggest that remote-sensing data combined with high-resolution numerical modeling and limited surface measurements might be able to define pollutant transport in large bodies of water as well as methods that rely only on more extensive surface measurements.

337 Detection of Landslide Areas Using Satellite Radar Interferometry
Hiroshi Kimura and Yasushi Yamaguchi

Abstract
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Three interferograms constructed from JERS-1 SAR data collected from June to October, 1995 were used to analyze the Itaya landslide in Japan by the three-pass method and the digital elevation model elimination (DEME) method. The differential interferograms produced by the three-pass method indicate only the extent of the displacement field, and fine geometrical features can not be recovered. In contrast, those produced by the DEME method indicate the different mechanical behaviors of the displacement from June to September and September to October, suggesting the existence of several subblocks in the landslide and the combination of irregular subblock movements and steady-state movement of the entire block. The interferograms and the precipitation record allow us to construct a preliminary model with sub-block movements along shallow slip planes during a larger precipitation period and steady-state movement of the major landslide block along the deep arcuare slip plane. SAR interferometry can reveal the behavior of the landslide that could not be observed with the discrete GPS  measurements of July to October, 1996.
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