449 Development of a Robust Algorithm for Transformation
of a 3D Object Point onto a 2D Image Point for Linear Pushbroom
Imagery
Taejung Kim, Dongseok Shin, and Young-Ran Lee
Abstract
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A powerful and robust algorithm for the Indirect Method, i.e., the transformation
of a 3D object point onto a 2D image point for linear pushbroom imagery,
is proposed. This algorithm solves the transformation iteratively with an
initial estimate of the 2D image point coordinates. However, this algorithm
does not require any sophisticated procedures to determine a "good" initial
estimate and it always converges to the correct solution. This algorithm
works using the following procedures:
first, with an (random) initial estimate of the 2D image point coordinates,
calculate the attitude of the camera platform; second, with the given attitude,
calculate the position of the camera platform and the 2D image point;
and third, update the estimate with the calculated 2D image point coordinates
and then go back to the first procedure and continue iteration until the estimated
and calculated image point coordinates converge. Results of the experiment
show that this algorithm converges very fast even when the initial estimate
has a huge error.
453 Image Matching Based on Tracking Matching Paths in the Similarity Space
Xueliang Mei, Peng Gong, and Greg S. Beging
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In this paper, we explore the feasibility of implementing surface continuity
and ordering constraints by tracking connected local peak points in the space
of matching similarity. We present a new image matching algorithm based on
match paths directly extracted in the similarity space. The main advantage
of these kinds of tokens over tokens extracted from the left and right images
is that the geometric distortions caused by perspective effects and description
inconsistency caused by independent extraction of tokens in the left and
right images are automatically eliminated. Through the tracking process,
the computation is greatly reduced. In addition, global information available
to support a local match for resolving matching ambiguities is fully utilized
in such a way that unrelated global information is excluded. Thus, the new
image matching algorithm is reliable and efficient. By eliminating the interpolation
process at the levels except the finest, the occluded regions and depth discontinuities
can be well localized.
461 Harmonic Analysis of Time-Series AVHRR NDVI Data
Mark E. Jakubauskas, David R. Legates, and Jude H. Kastens
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Harmonic analysis of a one-year time series (26 periods) of NOAA AVHRR NDVI
biweekly composite data was used to characterize seasonal changes for natural
and agricultural land use/land cover in Finney County in southwest Kansas.
Different crops (corn, soybeans, alfalfa) exhibit distinctive seasonal patterns
of NDVI variation that have strong periodic characteristics. Harmonic analysis,
also termed spectral analysis or Fourier analysis, decomposes a time-dependent
periodic phenomenon into a series of sinusoidal functions, each defined by
unique amplitude and phase values. The proportion of variance in the original
time-series data set
accounted for by each term of the harmonic analysis can also be calculated.
Amplitude and phase angle images were produced from analysis of the time-series
NDVI data and correlated with information on crop type and extent for the region
to develop a methodology for crop-type identification. Crop types occurring
in southwest Kansas, including corn, winter wheat, alfalfa, pasture, and native
prairie grasslands, were characterized and identified using this technique
and biweekly AVHRR composite data for 1992. For crops with a simple phenology,
such as corn, the majority of the variance was captured by the first and additive
terms of the harmonic analysis, while winter wheat exhibited a bimodal NDVI
periodicity with the majority of the variance accounted for by the second harmonic
term.
471 Zoning Land for Agricultural Protection by the Integration of Remote Sensing,
GIS, and Cellular Automata
Xia Li and Anthony Gar-On Yeh
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Zoning strategic agricultural land for protection has become important in reducing
agricultural land loss in rapidly growing areas. In this paper, a constrained
CA model based on the integration of remote sensing, GIS , and cellular automata
(CA) techniques was developed to overcome the limitations of the existing
methods commonly used by planners in zoning land for agricultural protection.
Remote sensing data were used to calculate the normalized difference vegetation
index (NDVI)
which was the initial map used for the model. The factors of land suitability
and geometry were embedded in the model to facilitate the rational allocation
of land for agricultural protection. The CA model was implemented within a
geographic information system which provided useful constraint information
and modeling environment. "Grey cells" were defined in the CA model to improve
modeling accuracy. The model has been tested in the Pearl River Delta, one
of the fastest growing areas in China.
479 Incidence Angle Correction of AirSAR Data to Facilitate Land-Cover Classification
Carl H. Menges, Greg J.E. Hill, Waqar Ahman, and Jakob J. van Zyl
Abstract
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Three image-based methods for correcting the effect of changes in incidence
angle on backscatter data are proposed and evaluated for AirSAR data of a
coastal tropical savanna landscape in Australia's Northern Territory. These
correction methods require little field knowledge and do not assume a linear
relationship between SAR backscatter and incidence angle. The correction
methods are applied to five independent components of the Stokes Matrix.
The results are evaluated using an existing land-cover classification to
extract mean backscatter values for individual land-cover classes before
and after the correction procedures. It is shown, for the
vegetation communities involved, that the slope method provides a successful
correction for the amplitude components of the backscatter data. The real and
imaginary parts of the co-polarized returns are best corrected using the LUT
method. The proposed correction procedure allowed the use of a maximum-likelihood
classification for the discrimination of ten land-cover types with an overall
accuracy of 87 percent across the complete swath width of the AirSAR data.
491 Mapping Gold-Bearing Massive Sulfide Deposits in the Neoproterozoic Allaqi
Suture, Southeast Egypt with Landsat TM and SIR-C/X SAR Images
Talatt M. Ramadan, Mohamed G. Abdelsalam, and Robert J. Stern
Abstract
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Meta-volcanic sequences in the Neoproterozoic Arabian-Nubian Shield host auriferous
massive sulfide deposits with surface expression in the form of clay and
iron alteration zones. These are large enough (few hundreds of meters across)
and have distinctive characteristic reflectance spectra to be mapped with
the 30-m spatial resolution Landsat Thematic Mapper (TM) images. Landsat
TM together with Shuttle Imaging Radar (SIR)-C/X-Synthetic Aperture Radar
(SAR) images are used for finding and mapping the alteration zones in the
western part of the east-trending Allaqi suture in the Southeastern Desert
of Egypt. The 5/7-5/1-3/4*5/4 band-ratio Landsat TM image shows the Umm Garaiat
alteration zone as sugary white; this appears red in the 5/7-4/5-3/1 band-ratio
Landsat TM image. Geological and geochemical data indicate that the Umm Garaiat
alteration zone is the surface expression of a massive sulfide deposit that
contains up to 12 g/t gold. Density slicing using 5/7 and 3/1 Landsat TM
band-ratios effectively maps clay and iron alteration. The 5/7 density slicing
Landsat TM image suggests that the Umm Garaiat
alteration zone is dominated by clay minerals. The 3/1 density slicing Landsat
TM image shows little evidence for FeO minerals associated with the Umm Garaiat
alteration zone. Analysis of Landsat TM images with supervised classification
techniques using the Umm Garaiat alteration zone as the training site helped
identify previously unknown alteration zones at Wadi Marahiq. Interpretation
of Chh-Lhh-Lhv SIR-C/X-SAR images helped in understanding the lithological
and structural
controls on massive sulfide deposits in the study area. This demonstrates the
utility of orbital remote sensing for finding ore deposits in arid regions.
499 Introducing New Indices for Accuracy Evaluation of Classified Images Representing
Semi-Natural Woodland Environments
Sotirios Koukoulas and George Alan Blackburn
Abstract
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A range of accuracy indices for determining the optimal outputs from the classification
of multispectral remotely sensed data is evaluated. Airborne Thematic Mapper
imagery of semi-natural woodland was used in conjunction with an in situ
data set. Indices of classification accuracy were unable to distinguish substantial
differences in classified images because they are based only on errors of
omission, accounting for only a proportion of the errors in classification.
The Classification Success Index (CSI) is introduced here to estimate the
overall effectiveness of classification, considering all output classes and
using both errors of omission and commission from the error matrix. The Individual
Classification Success Index (ICSI) is introduced which accounts for the
classification success of a specific class. Finally, the Group Classification
Success Index (GCSI) measures classification success for the most important
classes in the area of interest. These new indices were found to offer considerable
improvement over existing approaches.
511 Contour Smoothing by an Eclectic Procedure
Albert H.J. Christensen
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A procedure that simply and effectively smoothes the contour lines derived
from triangular irregular networks (TIN) is presented here. This procedure
is shown to use both the TIN and its linearly interpolated contours (raw
contours), which puts this process somewhere between the two smoothing approaches
currently in use. Hence, the qualification of eclectic. The two approaches
currently in use, smoothing of contours one at the time and independently
of the others in the contour set, and contouring of smooth patches, are discussed
with reference to objections that have been raised because of their shortcomings.
The eclectic procedure presented in this paper is described as a simple splicing
of arcs of quadratic parabolas, which gives an elegant look to the finished
product and ensures that all source data elements are scrupulously honored.
Additionally, the procedure is said to minimize the departures of the smoothed
contours from the linear model embodied in the TIN . A simple modification
to the basic procedure illustrates the manner in which the smoothing effect
can be varied at will.
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