Peer-Reviewed Articles
1017 Zoom-Dependent Camera Calibration in Digital
Close-Range Photogrammetry
C.S. Fraser and S. Al-Ajlouni
Abstract Download Full Article
One of the well-known constraints applying to the adoption
of consumer-grade digital cameras for photogrammetric
measurement is the requirement to record imagery at fixed
zoom and focus settings. The camera is then calibrated for
the lens setting employed. This requirement arises because
calibration parameters vary significantly with zoom/focus
setting. In this paper, a zoom-dependent calibration process
is proposed whereby the image coordinate correction model
for interior orientation and lens distortion is expressed as
a function of the focal length written to the EXIF header of
the image file. The proposed approach frees the practitioner
from the requirement to utilize fixed zoom/focus settings for
the images forming the photogrammetric network. Following
a review of the behavior of camera calibration parameters
with varying zoom settings, an account of the newly developed
zoom-dependent calibration model is presented. Experimental
results of its application to four digital cameras are
analysed. These show that the proposed approach is suited
to numerous applications of medium-accuracy, digital, closerange
photogrammetry.
1027 A 16-year Time Series of 1 km AVHRR Satellite Data of
the Conterminous United States and Alaska
Jeff Eidenshink
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The U.S. Geological Survey (USGS) has developed a 16-year
time series of vegetation condition information for the conterminous
United States and Alaska using 1 km Advanced
Very High Resolution Radiometer (AVHRR) data. The AVHRR
data have been processed using consistent methods that
account for radiometric variability due to calibration uncertainty,
the effects of the atmosphere on surface radiometric
measurements obtained from wide field-of-view observations,
and the geometric registration accuracy. The conterminous
United States and Alaska data sets have an atmospheric
correction for water vapor, ozone, and Rayleigh scattering
and include a cloud mask derived using the Clouds from
AVHRR (CLAVR) algorithm. In comparison with other AVHRR
time series data sets, the conterminous United States and
Alaska data are processed using similar techniques. The
primary difference is that the conterminous United States
and Alaska data are at 1 km resolution, while others are
at 8 km resolution. The time series consists of weekly and
biweekly maximum normalized difference vegetation index
(NDVI) composites.
1037 Benthic Habitat Mapping in Tropical Marine
Environments Using QuickBird Multispectral Data
Deepak Mishra, Sunil Narumalani, Donald Rundquist, and
Merlin Lawson
Abstract Download Full Article
The objective of this research focused on the utility of
QuickBird multispectral data for identifying and classifying
tropical-marine benthic habitats after applying atmospheric
and water-column corrections for an area around Roatan
Island, Honduras. Atmospheric (Rayleigh and aerosol path
radiance) and water column corrections (water depth and
water column attenuation) were applied to the imagery,
making it an effective method for mapping benthic habitats.
Water depth for each pixel was calculated based on a
linear model by regressing transformed radiance over known
homogenous benthos against measured depths. Water
column correction was achieved by deriving absorption and
backscattering coefficients for each band of the image using
a 50 x 50 window of clear water pixels. Corrections for
water path radiance and water column attenuation of the
bottom reflected radiance were made for the entire scene,
allowing the bottom albedo to be determined for shallow
coastal areas. An image of the bottom (i.e., an albedo image),
minus the water column, was produced. Albedos were ≤8
percent for seagrass benthos, approximately 8 to 18 percent
for coral areas, and ≥18 percent for sand dominated areas.
An unsupervised classification algorithm was applied to the
bottom albedo image, generating a classified map of benthic
habitats. Accuracy assessment based on 383 reference points
revealed an overall accuracy of 81 percent, with an overall
Kappa value of 0.774.
1049 Automatic Registration of Airborne Images with
Complex Local Distortion
Desheng Liu, Peng Gong, Maggi Kelly, and Qinghua Guo
Abstract Download Full Article
Accurate registration of airborne images is challenging
because complex local geometric distortions are often
involved in image acquisition. In this paper, we propose
a solution to this registration problem in two parts. First,
we present an area-based method to extract sufficient numbers
of well-located control points, and second, we use the
extracted control points with local transformation models to
register multi-temporal airborne images. The proposed image
registration methods were applied to two airborne images
with complex local distortion. Performance was evaluated
and compared using different transformation models (global
models and local models), different numbers of control
points, and different similarity measures (correlation coefficient
and mutual information). The results showed that
local models outperformed global models, more control
points could significantly improve local transformation
models but not on the global transformation models, and
two similarity measures performed similarly. These results
revealed two important findings: first, the area-based methods
generated larger amounts of evenly distributed control
points; and second, local transformation models achieved
better registration accuracy when larger amount of evenly
distributed control points are used. We concluded that the
combination of area-based control point extraction with
local transformation models is effective for the registration
of airborne images with complex local distortion.
1061 Orientation of Ground-level Motion Imagery Using
Building Facades
Anthony Stefanidis, Charalampos Georgiadis, and Peggy
Agouris
Abstract Download Full Article
In this paper, we address the orientation of ground-level
motion imagery captured by sensors roaming in an urban
area. We investigate the use of building façades (instead of
traditional points), as matching features for ground-level
motion imagery orientation. We assume a situation where
few images in our sequence are already absolutely oriented,
and present a novel approach to orient all remaining inbetween
image sequences relative to them. This innovative
version of dependent orientation allows us to propagate
orientation information within sequences of ground level
imagery, establishing a novel orientation scheme. Experimental
results show accuracies on the order of 0.18 to 0.29
degrees in rotation estimation, and 0.17 to 0.29 meters in
camera position determination.
1073 A User-customized Web-based Delivery System of Hypertemporal
Remote Sensing Datasets for Australasia
Michael Schmidt, Edward A. King, and Tim R. McVicar
Abstract Download Full Article
Long time series of well-calibrated and consistent daily
remote sensing data are important for studies of intra-and
inter-annual environmental behavior. These data are used
to support environmental management, and in most locations
are the only historical spatial dataset. The Web-CATS
(CSIRO AVHRR Time Series) system provides access to the
Australasian Advanced Very High Resolution Radiometer
(AVHRR) data archive using the World Wide Web. The data
archive consists of multiple daily satellite overpasses from
several receiving stations in Australia since July 1981. The
data are held online enabling the use of state-of-the-art
algorithms to generate on-demand user-customized products.
This novel design for operational and dynamic remote
sensing data product generation enables Web-CATS users to
browse the entire metadata-database and produce consistent
time series information from on-line data in near real time.
As these algorithms improve, users have the ability to easily
re-process their dataset(s).
1081 Quantifying DEM Uncertainty and Its Effect on
Topographic Parameters
Suzanne P. Wechsler and Charles N. Kroll
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Digital elevation models (DEMs) are representations of topography
with inherent errors that constitute uncertainty. DEM
data are often used in analyses without quantifying the
effects of these errors. This paper describes a Monte Carlo
methodology for evaluation of the effects of uncertainty
on elevation and derived topographic parameters. Four
methods for representing DEM uncertainty that utilize metadata
and spatial characteristics of a DEM are presented.
Seven statistics derived from simulation results were used
to quantify the effect of DEM error. When uncertainty was
quantified by the average relative absolute difference, elevation
did not deviate. The range of deviation across
the four methods for slope was 5 to 8 percent, 460 to 950
percent for derived catchment areas and 4 to 9 percent for
the topographic index. This research demonstrates how
application of this methodology can address DEM uncertainty,
contributing to more responsible use of elevation
and derived topographic parameters, and ultimately results
obtained from their use.