Peer-Reviewed Articles
1333 Landsat Coverage of the Earth at
High Latitudes
Robert Bindschadler
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Overlapping coverage of Landsat imagery at high latitudes is examined systematically
and quantitatively. The Earth is separated into "row strips" aligned
with the Landsat World Reference System (WRS), and the multi-scene coverage
of Landsat imagery is divided into three types of areas: extended, missing,
and overlap. Varying image orientation and narrowing row-strip width with
increasing latitude are shown to have major impacts on these three areas.
The dependencies of these coverage areas on skipping image collections from
adjacent paths are calculated. This forms the basis for sampling strategies
that can significantly reduce the number of images required to obtain full
ground coverage at high latitudes. The calculations show that Antarctica
can be covered with approximately one-third the total number of scene opportunities.
1341 Block Bundle Adjustment of Landsat 7 ETM+
Images over Mountainous Areas
Thierry Toutin
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This research study showed the potential of block bundle adjustment with nadir
viewing sensor images, such as Landsat 7 ETM+. The method is based on the
3D analytical geometric model developed for multisensor images at the Canada
Centre for Remote Sensing, Natural Resources Canada. Different block sizes
and configurations were tested and compared using an image bundle adjustment.
The different tests using 15 Landsat 7 ETM+ images (five paths and three
rows) acquired over a study site in the Canadian Rocky Mountains, showed
that the same results (around 25-m errors) could be obtained with image blocks
as with a single image using a largely reduced number of ground control points
(GCPs). However, the combined image measurement and map errors of GCPs were
included in the final error budget, and the internal accuracy of the blocks
should be better (around one pixel or less). The number of GCPs to be used
depended mainly on the cartographic data accuracy: more GCPs than the minimum
required reduced the error propagation in the least-squares block bundle
adjustment. In addition, tie points with a known elevation value (elevation
tie points, ETPs) instead of normal tie points were used to link the adjacent
images/strips (north- south and east-west) because the viewing-angle differences
of overlapping images were smaller than 1° in north-south overlaps and
around 10° in east-west overlaps. Better and more consistent results
were also obtained using strips of images in the blocks acquired from the
same orbit and date instead of using independent images. Finally, using only
GCPs in the outer strips/images and ETPs in each overlap achieved the same
results (25-m errors).
1351 Line-Based Modified Iterated Hough Transform
for Autonomous Single-Photo Resection
Ayman F. Habib, Hsiang Tseng Lin, and Michel F. Morgan
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Automatic single photo resection (SPR) remains to be one of the challenging
problems in digital photogrammetry. Earlier attempts to automate the space
resection task were mainly point-based, where image-point primitives are
first extracted and matched with their object counterparts. The matched primitives
are then used to estimate the exterior orientation parameters (EOP). However,
visibility and uniqueness of distinct control points in the input imagery
limit robust automation of the pose estimation procedure. Recent advances
in digital photogrammetry mandate adopting higher-level primitives such as
control linear features replacing traditional control points. Linear features
can be automatically extracted in image space. On the other hand, object-space
control linear features can be extracted from an existing GIS layer containing
3D vector data such as a road network and/or terrestrial mobile mapping systems
(MMS). In this paper, we present a line-based approach for simultaneously
determining the position and attitude of the involved imagery as well as
establishing the correspondence between image- and object-space features.
This approach is motivated by the fact that captured imagery over a man-made
environment is rich in straight-line segments. Moreover, free-form linear
features can be reliably represented with sufficient accuracy by a sequence
of straight-line segments (i.e., polylines). The suggested methodology starts
by establishing a general mathematical model for relating conjugate straight-line
segments to the EOP of the image under consideration. Then, a Modified Iterated
Hough Transform (MIHT) strategy is adopted to derive the correspondence between
image and object primitives as well as the position and the attitude of the
involved imagery. This approach does not necessitate having one-to-one correspondence
between image- and object-space primitives, which makes it robust against
changes and/or discrepancies between the primitives. The parameter estimation
and matching processes follow an optimum sequential procedure, which depends
on the sensitivity of the mathematical model, relating corresponding primitives
with different orientation at various image regions, to incremental changes
in the EOP. Experimental results using real data proved the feasibility and
robustness of the proposed approach even in the presence of a large percentage
of outliers and/or discrepancies between the image-and object-space features.
1359 Analysis of Terrain Elevation Effects on Ikonos
Imagery Rectification Accuracy by Using Non-Rigorous Models
Wenzhong Shi and Ahmed Shaker
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In the absence of sensor calibration and satellite orbit information for Ikonos
satellite imagery, empirical methods have to be adopted for the geometric
correction of the images. This paper addresses two major terrain related
issues. First, the paper focuses on the effects of terrain variation on the
rectification accuracy of Ikonos images using various two-dimensional (2D)
transformation models. It was found that (1) the accuracy of rectified coordinates
is significantly affected by elevation differences-the greater the differences,
the lower the rectified accuracy; (2) for higher accuracy results, ground
control points (GCPs) should be projected to a compensation plane before
2D transformation models are applied; and (3) an accuracy of about 0.5 m
RMS error can be gained from rectified Ikonos images by utilizing most 2D
transformation models when accurate ground control points are available.
Second, the paper addresses the effects of terrain variation and the number of GCPs on the obtained ground points accuracy when an eight-parameter affine model is used for 3D ground points determination for stereoscopic Ikonos imagery. It was found that (1) non-collinearity-based 3D orientation and triangulation model can be used successfully in most cases for 3D ground point determination without the need for a camera model or satellite ephemeris data; (2) accuracy up to the sub-pixel level in the X-Y directions and about one pixel in the Z direction can be achieved; (3) the model works significantly better for hilly and mountainous areas than very flat areas; and (4) the accuracy of the results can be improved significantly either by increasing the number of GCPs or by adding topographic constraints.
1367 Comparison of Digital Elevation Models for
Aquatic Data Development
Sharon Clarke and Kelly Burnett
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Thirty-meter digital elevation models (DEMs) produced by the U.S. Geological
Survey (USGS) are widely available and commonly used in analyzing aquatic
systems. However, these DEMs are of relatively coarse resolution, were inconsistently
produced (i.e., Level 1 versus Level 2 DEMs), and lack drainage enforcement.
Such issues may hamper efforts to accurately model streams, delineate hydrologic
units (HUs), and classify slope. Thus, the Coastal Landscape Analysis and
Modeling Study (CLAMS) compared streams, HUs, and slope classes generated
from sample 10-meter drainage-enforced (DE) DEMs and 30-meter DEMs. We found
that (1) drainage enforcement improved the spatial accuracy of streams and
HU boundaries more than did increasing resolution from 30 meters to 10 meters,
particularly in flatter terrain; (2) streams and HU boundaries were generally
more accurate when delineated with Level 2 than with Level 1 30-meter DEMs;
and (3) the 10-meter DE-DEMs better represented both higher and lower slope
classes. These findings prompted us to have 10-meter DE-DEMs produced for
the Coast Range Province of Oregon, increased confidence in CLAMS outputs
from the 10-meter DE-DEMs, and should benefit others interested in using
DEMs for aquatic analyses.
1377 Mapping Urban Areas by Fusing Multiple Sources
of Coarse Resolution Remotely Sensed Data
Annemarie Schneider, Mark A. Friedl, Douglas M. McIver, and Curtis E. Woodcock
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In recent decades, rapid rates of population growth and urban expansion have
led to widespread conversion of natural ecosystems and agricultural lands
to urban land cover. The amount and rate of this land conversion affects
local and regional ecosystems, climate, biogeochemistry, as well as food
production. The main objective of the research described in this paper is
to improve understanding of the methodological and validation requirements
for mapping urban land cover over large areas from coarse resolution remotely
sensed data. A technique called boosting is used to improve supervised classification
accuracy and provides a means to integrate MODIS data with the DMSP nighttime
lights data set and gridded population data. Results for North America indicate
that fusion of these three data types improves urban classification results
by resolving confusion between urban and other classes that occurs when any
one of the data sets is used by itself. Traditional measures of accuracy
assessment as well as new, maplet-based methods demonstrate the effectiveness
of the methodology for creating maps of cities at continental scales.
1387 A State-Level Comparative Analysis of the
GAP and NLCD Land-Cover Data Sets
Brian D. Wardlow and Stephen L. Egbert
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Two nationwide land-cover mapping efforts, the GAP Analysis Program (GAP) and
the USGS National Land Cover Data (NLCD) program, address the need for intermediate-scale
land-cover information to support a diverse user community. The data sets
are comparable, but have different objectives, classification systems, and
methodologies. A comparative analysis of the GAP and NLCD data sets is needed
throughout the United States to determine their relative strengths and limitations
and better inform the user community of their applicability for various applications.
This study conducted comparative analyses of the GAP and NLCD data sets for
Kansas. The data sets were generalized to a common set of land-cover classes,
and pixel-level comparisons were made at the state and ecoregion levels.
The GAP and NLCD had an overall classification agreement of 67 percent at
the state level, with most of the classification disagreement occurring between
cropland and grassland. The cropland area classified by GAP was comparable
to cropland area estimates reported by the USDA, while NLCD appeared to underestimate
cropland and overestimate grassland. The single-date/multiple-data source
classification approach and the sub-optimal early-spring dates of Landsat
TM data used to produce NLCD resulted in substantial confusion in cropland-grassland
discrimination. The multiple-date classification approach used by Kansas
GAP provided better discrimination of most land-cover classes. Some classification
disagreement, however, was attributable to methodological differences between
GAP and NLCD. Accuracy assessment found an overall accuracy of 87 percent
for GAP and 81 percent for NLCD, and GAP had higher accuracies for most individual
land-cover classes. The Kansas GAP and NLCD land-cover products were found
to be comparable in terms of characterizing broad scale land-cover patterns,
but the Kansas GAP land-cover map appears to be more appropriate for localized
applications that require detailed and accurate land-cover information.
1399 A Comparison of Vector and Raster GIS Methods
for Calculating Landscape Metrics Used in Environmental Assessments
Timothy G. Wade, James D. Wickham, Maliha S. Nash, Anne C. Neale, Kurt H. Riitters,
and K. Bruce Jones
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GIS-based measurements that combine native raster and native vector data are
commonly used in environmental assessments. Most of these measurements can
be calculated using either raster or vector data formats and processing methods.
Raster processes are more commonly used because they can be significantly
faster computationally than vector, but error is introduced in converting
vector data to raster. This conversion error has been widely studied and
quantified, but the impact on environmental assessment results has not been
investigated. We examined four GIS-based measurements commonly used in environmental
assessments for approximately 1000 watersheds in the state of Maryland and
Washington, D.C. Each metric was calculated using vector and raster methods,
and estimated values were compared using a paired t-test, Spearman rank correlation,
and cluster analyses. Paired t-tests were used to determine the statistical
significance of quantitative differences between methods, and Spearman rank
correlation and cluster analyses were used to evaluate the impact of the
differences on environmental assessments. Paired t-test results indicated
significant quantitative differences between methods for three of the four
metrics. However, Spearman ranks and cluster analyses indicated that the
quantitative differences would not affect environmental assessment results.
Spearman rank correlations between vector and raster values were greater
than 0.98 for all comparisons. Cluster analyses resulted in identical assignment
for 88 percent to over 98 percent of watersheds analyzed among vector and
various raster methods
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