Peer-Reviewed Article Abstracts
385 Rigorous Mathematical Modeling of Airborne Pushbroom
Imaging Systems
Changno Lee, Henry J. Theiss, James S. Bethel, and Edward M. Mikhail
Abstract
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Airborne pushbroom imaging systems are becoming increasingly of interest
for panchromatic, multispectral, and hyperspectral applications.
The source imagery for this paper is from the HYDICE (Hyperspectral
Digital Imagery Collection Experiment) sensor, developed by the Naval
Research Laboratory at Stennis Space Center. The primary focus of
this paper is to present rigorous mathematical models that rectify
a single band of HYDICE imagery so that each pixel in the image
can be accurately transformed to its ground location. Equations are
presented for a piecewise polynomial model and a Gauss-Markov model.
The implementation of the mathematical modeling of straight linear
features into the rectification using either model is discussed.
The valuable contribution of linear features and the superior performance
of the Gauss-Markov model are shown in tables as well as in orthorectified
images that compare the results to those from simpler models.
393 Accurate Orientation for Airborne Mapping Systems
Jan Skaloud and Klaus-Peter Schwarz
Abstract
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Stringent requirements on the accuracy of attitude determination are
currently a major challenge for strapdown INS/GPS integration, which
is at the core of self-contained airborne remote sensing and mapping
systems. This paper reviews the error models for INS/GPS integration
and focuses in detail on designing filtering methods for improving
attitude accuracy in the bandwidth in which an inertial system does
not benefit from frequent GPS position/velocity updates. Several
filtering methods are designed based on the spectral analysis of
the raw inertial signal in a dynamic environment. These include a
spectral technique for dither spike removal and a class of low-pass
finite-impulse-response (FIR) filters operating in forward/backward
manner for achieving zero phase distortion. The orientation performance
of the whole system with different filters is evaluated by comparing
it to the "true" attitude information provided by a photogrammetric
block adjustment. Results show clearly that the choice of an appropriate
filter is decisive for attitude accuracy. Overall, the INS/GPS integration
combined with the most suitable pre-filtering method agrees with
the external orientation reference to 0.005º (19") RMS over
the whole test period, while the flight-line consistency is typically
0.003º (10") RMS. The best filter in the comparison has an RMS
seven times smaller than the Butterworth filter which is frequently
applied in the industrial designs of INS.
403 Contributions
of Differential GPS and GLONASS Observations to
Point Accuracy under Forest Canopies
Eric Næsset, Trygve Bjerk, Ola Øvstedal, and Lorentz H.
Ryan
Abstract
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A 24-channel, single-frequency receiver observing the C/A code and carrier
phase of both GPS and GLONASS was used to determine the positional
accuracy of 27 points under tree canopies. The mean positional accuracy based
on combined differential postprocessing of GPS C/A code and carrier
phase observations ranged from 0.20 m to 5.72 m for 2.5 min to 30 min of
observation at points with basal area ranging from <15 m²/ha to >25
m²/ha. The mean positional accuracy of combined differential postprocessing
of GPS+GLONASS C/A code and carrier phase observations ranged from
0.09 m to 2.85 m. The accuracy increased with decreasing density of forest
and improving geometric satellite distribution as observed at the base station.
Static differential postprocessing of 30-min observations of GPS+GLONASS carrier
phase gave fixed solutions for 13 of the 27 points. The accuracy of these
solutions ranged from 0.01 m to 0.09 m. The probability of obtaining a fixed
solution under tree canopies was modeled by logistic regression. The regression
model classified correctly 81.5 percent of the processed solutions.
409 Accuracy Assessment of Wetland Boundary Delineation Using Aerial
Photography and Digital Orthophotography
Jeffrey Barrette, Peter August, and Francis Golet
Abstract
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We compared the horizontal accuracy of forested wetland boundary delineations
obtained from large-scale, natural color aerial photography against delineations
obtained from "heads-up" digitizing of digital orthophotography. The absolute
value of the mean (± SD) distance between the field-derived "true" wetland
boundary location and the orthophotograph-derived wetland boundaries was
3.4 ± 3.4 m and was slightly more accurate than the mean distance
between the "true" boundary and the aerial-photo-derived wetland boundaries
(4.5 ± 4.0 m). Field visitation increased the accuracy of delineating
wetland boundaries, and the majority of wetland edges-both orthophotograph-
and photo-derived-were placed on the wetland side relative to the `true'
boundary.
417 Detecting Ice-Sheet
Topography with AVHRR, RESURS-01, and Landsat
TM Imagery
Robert Bindschadler and Patricia Vornberger
Abstract
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The ability of different visible-band satellite imagers to detect subtle ice-sheet
topographic features is examined by both qualitative and quantitative comparisons.
The AVHRR 10-bit sensor is shown to have the best radiometric resolution,
but its poorer spatial resolution limits this sensor's ability to discriminate
smaller scale topography. RESURS-01 is a less well known 8-bit sensor,
but this instrument's higher noise and poorer radiometric resolution restrict
its utility for ice-sheet research. Landsat TM applies 8-bit quantization
over a narrower radiometric range, causing it to saturate for some conditions.
This limitation allows TM to achieve a radiometric resolution half
that of AVHRR while retaining a much higher spatial resolution. No
SPOT imagery was compared, but the sensor is shown to have less radiometric
resolution than TM . However, SPOT has better spatial resolution and
is less likely to saturate.
423 Predicting the Distribution of Eurasian Badger (Meles meles) Setts
over an Urbanized Landscape: A GIS Approach
Amanda Wright, Alan H. Fielding, and C. Philip Wheater
Abstract
The distribution of the Eurasian badger within an urbanized county (Greater
Manchester, United Kingdom) was investigated through the development of a
predictive model. Badger main sett distribution was taken as a surrogate
of badger social group distribution, with the recognition of the importance
of main setts as a limiting resource for badger distribution. The model utilized
a range of environmental data layers within a GIS (land cover, soil, slope,
and elevation). The data were transformed using principal components analysis
to produce a reduced set of uncorrelated, normally distributed environmental
variables. Predictive discriminant analysis was used to construct the model
by discriminating main sett sample sites from random non-sett sites. The
model classified over 80 percent of sites correctly and was validated using
external analysis. A visual representation of the model was produced through
interpolating within a GIS a discriminant surface from the discriminant scores
of the model.
429 Multispectral Satellite Image and Ancillary Data Integration for
Geological Classification
Evaristo Ricchetti
Abstract
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Digital classification of Landsat imagery for geological purposes often gives
poor results. To improve classification accuracy, spectral data have been
combined with ancillary data. These data have been used in pre-classification
processing to enhance image quality, and as additional attribute information
during the classification process. Several geological classifications were
conducted using various levels of integrated spectral and topographic data.
A slope map was used to add information about the geomorphologic nature of
the different geological units. Logical channel and stratification methods
were applied and compared to a spectral classification. The classification
results demonstrate that a significant increase in overall accuracy can be
achieved by combining topographic data with spectral data. The use of stratification,
in addition to a logical channel, did not give an evident improvement in
overall accuracy. The use of ancillary data in image classification must
rely on in-depth knowledge of the target to select the attribute that best
characterizes it.
437 Integrating Landsat, Geologic, and Airborne Gamma Ray Data as an
Aid to Surficial Geology Mapping and Mineral Exploration in the Manitouwadge
Area, Ontario
I.M. Kettles, A.N. Rencz, and S.D. Bauke
Abstract
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For surficial mapping and mineral prospecting purposes, Landsat Thematic Mapper,
airborne gamma ray spectrometry, and geological data were integrated for
a 5000-km² area near Manitouwadge, Ontario. Using characteristic Landsat
data signatures for the main surficial units, the signatures for 6,250,000
30-by 30-m-pixel areas were evaluated, and each pixel area was assigned to
a surficial unit category. When the predictive surficial geology map thus
generated was compared to eight surficial geology units on a published surficial
geology map, there were obvious visual similarities, with an overall pixel-by-pixel
accuracy of 46 percent. Pixel areas with Landsat and gamma ray signatures
comparable to those of training sites in base metal-enriched tills near the
Manitouwadge area mines, commonly formed clusters or near-linear bands overlying
Archean greenstone belts or in close contact with a carbonatite complex where
Fe and Zn mineralization is known. Tests on these derivative pixel areas
indicated that their distribution was controlled almost entriely by the gamma
ray data signatures.
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