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