Peer-Reviewed Articles
689 Lineal Feature Detection Using Multiresolution
Wavelet Filters
Samuel P. Kozaitis and R. H. Cofer
Abstract Download
Full Article
We detected road pixels in aerial imagery using a multi-resolution, wavelet-based
approach. Our method involved
the description of a differential geometry approach for road
seed pixel detection in terms of wavelet transforms. Using
this approach allowed us to extend the differential geometry
approach to incorporate multiple scales. We found that
using multiple scales significantly reduced the number of
potential false positives. Our approach seemed to work well
with a computer-assisted approach where the “seed” or
potential pixels of interest should have a high confidence
level of being correct. We found that our approach led to an
effective method for detecting roads in aerial imagery. Our
method is general, and in principle could be applied to
other filtering techniques besides the one used here.
699 Photogrammetric and Lidar Data Registration
Using Linear Features
Ayman Habib, Mwafag Ghanma, Michel Morgan, and Rami Al-Ruzouq
Abstract Download
Full Article
The enormous increase in the volume of datasets acquired
by lidar systems is leading towards their extensive exploitation in a variety
of applications, such as, surface reconstruction, city modeling, and generation
of perspective views.
Though being a fairly new technology, lidar has been influenced by and had
a significant impact on photogrammetry.
Such an influence or impact can be attributed to the complementary nature
of the information provided by the two
systems. For example, photogrammetric processing of
imagery produces accurate information regarding object
space break lines (discontinuities). On the other hand, lidar
provides accurate information describing homogeneous
physical surfaces. Hence, it proves logical to combine data
from the two sensors to arrive at a more robust and complete reconstruction
of 3D objects. This paper introduces
alternative approaches for the registration of data captured
by photogrammetric and lidar systems to a common reference frame. The first
approach incorporates lidar features as
control for establishing the datum in the photogrammetric
bundle adjustment. The second approach starts by manipulating the photogrammetric
imagery to produce a 3D model,
including a set of linear features along object space discontinuities, relative
to an arbitrarily chosen coordinate system.
Afterwards, conjugate photogrammetric and lidar straight
line features are used to establish the transformation between the arbitrarily
chosen photogrammetric coordinate
system and the lidar reference frame. The second approach
(bundle adjustment, followed by similarity transformation) is
general enough to be applied for the co-registration of multiple three-dimensional
datasets regardless of their origin
(e.g., adjacent lidar strips, surfaces in GIS databases, and
temporal elevation data). The registration procedure would
allow for the identification of inconsistencies between the surfaces in
question. Such inconsistencies might arise from changes taking place within
the object space or inaccurate
calibration of the internal characteristics of the lidar and the
photogrammetric systems. Therefore, the proposed methodology is useful for
change detection and system calibration
applications. Experimental results from aerial and terrestrial
datasets proved the feasibility of the suggested methodologies.
709 Mapping Detailed Biotic Communities in the
Upper San Pedro Valley of Southeastern Arizona using Landsat 7 ETM+ Data
and Supervised Spectral Angle Classifier
Youngsinn Sohn and Jiaguo Qi
Abstract Download
Full Article
In this study, we demonstrated that ecologically meaningful,
detailed biotic communities can be mapped with high
accuracy (85 percent) in a soil dominated semi-arid environment using a simple
supervised classification approach with Landsat TM data, if an appropriate
classification algorithm
and truly representative training signatures are applied. We
used the Supervised Spectral Angle Classifier by Sohn and
Rebello (2002) to map biotic communities in the Upper San
Pedro Valley, Arizona. By choosing an image acquisition
date (season) that can maximize the differentiation of
feature characteristics associated with each biotic community, and adopting
the Supervised Spectral Angle Classifier that is sensitive to the spectral
shape pattern, we were able
to map biotic communities without the secondary, derived
variables such as DEM, soil, and seasonal NDVI, seasonal
greenness indices to incorporate environmental factors and
phenological changes of vegetation into the classification
procedures. Biotic communities and land cover categories
mapped in this study include: Chihuahuan desert-scrub,
mesquite scrub, Chihuahuan semi-desert grassland (<30 percent grass-forbs
cover density, >30 percent grass-forbs
cove density, and disclimax), Madrean encinal woodland,
Madrean montane conifer forest, mesquite bosque, riparian
gallery, irrigated pasture/golf course, urban/developed, bare
soil, and water. Our study reaffirmed that the Spectral Angle
Classifier can potentially be one of the most robust and
accurate classifiers. Also, according to our study, the current
spatial, spectral, and radiometric characteristics of Landsat
TM data seem effective for mapping detailed vegetation
communities even in a semi-arid environment.
719 Analysis of Urban Land Cover and Population
Density in the United States
Francesca Pozzi and Christopher Small
Abstract Download
Full Article
In this study we investigate the question of whether urban
and suburban areas in the United States can be defined on
the basis of demographic and/or physical characteristics, in
particular, population density and vegetation abundance.
We investigate their relationship in the cities of Atlanta,
Chicago, Los Angeles, New York, Phoenix, and Seattle and
compare the results with the USGS National Land Cover
Dataset’s urban classes. The bimodal distribution of U.S.
population density provides a demographic basis for distinguishing rural
and suburban land use, while a distinct tail of high population densities
(>10,000 people/km<sup>2</sup>)
corresponds to high intensity urban residential cores. Results
show that the maximum vegetation fraction diminishes with
increasing population density, but the spectral heterogeneity
at pixel scales still results in a wide range of vegetation
fractions within demographically urban and suburban areas.
None of the USGS residential classes show a strong correspondence to either
vegetation fraction or population density. However, quantitative characterization
of vegetation abundance provides a
basis for comparison of the physical environments of suburban areas. We suggest
that classification schemes based
on spectral heterogeneity at multiple pixel scales, supplemented by auxiliary
data sources, may
provide a more accurate and self-consistent way to quantify
urban land use and analyze urban growth than traditional
thematic classification schemes.
727 A Photogrammetric Method for Single Image
Orientation and Measurement
Antonio Maria Garcia Tommaselli and Mário Luis Lopes Reiss
Abstract Download
Full Article
The aim of this paper is to present a photogrammetric method
for determining the dimensions of flat surfaces, such as
billboards, based on a single digital image. A mathematical
model was adapted to generate linear equations for vertical
and horizontal lines in the object space. These lines are
identified and measured in the image and the rotation matrix
is computed using an indirect method. The distance between
the camera and the surface is measured using a lasermeter,
providing the coordinates of the camera perspective center.
Eccentricity of the lasermeter center related to the camera
perspective center is modeled by three translations, which are
computed using a calibration procedure. Some experiments
were performed to test the proposed method and the achieved
results are within a relative error of about 1 percent in areas
and distances in the object space. This accuracy fulfills the
requirements of the intended applications.
733 Stability Analysis and Geometric Calibration
of Off-the-Shelf Digital Cameras
Ayman Habib and Michel Morgan
Abstract Download
Full Article
Recent developments of digital cameras in terms of the size
of a Charged Coupled Device (CCD) and Complementary Metal
Oxide Semiconductor (CMOS) arrays, as well as reduced costs,
are leading to their applications in traditional and new
photogrammetric, surveying, and mapping functions. Such
cameras require careful calibration to determine their metric
characteristics, as defined by the Interior Orientation Parameters (IOP),
which are essential for any photogrammetric activity. Moreover, the stability
of the estimated IOP of these
cameras over short and long time periods has to be analyzed
and quantified. This paper outlines the incorporation of
straight lines in a bundle adjustment procedure for calibrating off-the-shelf/low-cost
digital cameras. A framework for automatic extraction of the straight lines
in the images is also
presented and tested. In addition, the research introduces
new approaches for testing the camera stability, where the
degree of similarity between reconstructed bundles using two
sets of IOP is quantitatively evaluated. Experimental results
with real data proved the feasibility of the line-based self-calibration
approach. Analysis of the estimated IOP from various calibration sessions
over long time periods revealed
the stability of the implemented camera.
743 Neighborhood Systems for Airborne Laser
Data
Sagi Filin and Norbert Pfeifer
Abstract Download
Full Article
Analysis of common neighborhood definitions for airborne
laser data, triangulation or raster-based, reveals deficiencies in
modeling the measured objects. Concepts that originate from
2D data structures are used for modeling complex 3D objects
and for handling datasets with different point densities.
Realizing these shortcomings, this paper proposes a new
neighborhood system for airborne laser data. Based on laser
data characteristics the proposed systems consider, among
other features, point density, layered and overhanging structures, and local
surface trends. Parameters for the proposed systems are derived from theoretical
and practical observations. The paper
demonstrates the type of neighborhood that is established by the proposed
systems, and shows that artifacts that are
usually created by the common neighborhoods are avoided here, and that structures
within the data that are
usually masked are revealed. The paper demonstrates how
subsequent applications benefit from the new system. Finally,
the estimation of surface normals by the proposed systems is
compared to the triangulation; results show a significant
improvement in the reliability and quality of the estimation.