International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004
normalized correlation coefficients was performed in the raw
images. Based on ESRI ArcObjects and Microsoft.Net Cf
programming language, a shoreline extraction system was
developed to aid in shoreline digitizing, point matching, 3D
coordinate calculating, and result checking. 3-D coordinates of
the shoreline can be calculated from the matched image points in
the stereo images using RFCs supplied by the vendor (Li et al.,
2003). The refinement of the calculated coordinates was done by
applying a translation model in the object space as discussed
above. A transformation was carried out to convert the geographic
coordinates (latitude, longitude) into State Plane coordinates.
Figure 3 shows the calculated shoreline from the QuickBird
panchromatic stereo images along with the orthophoto generated
automatically using the OrthoBase module of ERDAS Imagine
8.6. It can be seen that the semiautomatic result fits very well with
the orthophoto.
CONCLUSIONS
This paper presents the experimental results of a study on
accuracy improvement of ground points determined by IKONOS
and QuickBird images using GCPs and different transformation
models in both object and image spaces. Different methods and
GCP distribution patterns are tested. Complete tables of
computational results are given for discussion as well as
supplying the reader with information for their own analysis. As
an application of the method, a 3-D shoreline was extracted from
QuickBird panchromatic stereo images. We can draw the
following conclusions based on the above experimental results.
In general, there are no significant differences in the results from
using the different models in the object or image space, although
the affine and higher-order polynomial models in the image space
require fewer GCPs than the models in object space. The models
are generally more stable in the image space, considering the
maximum differences observed. The quality of the IKONOS and
QuickBird images is excellent. Using a simple translation model
and one GCP we can correct the majority of errors and achieve a
good result. It is recommended that a scale and translation model
or an affine model with four to six well-distributed GCPs be used
to achieve a high level of accuracy. These methods seem to be
most practical for use in mapping applications.
The objects chosen in this study are general image features such
as road intersections, building corners, and other objects
distinguished in the coastal area. The precision of the image point
measurement is about one-half to one pixel. The accuracy
improvement method was then applied to 3D shoreline extraction.
The derived 3D shoreline from QuickBird stereo images reached
a ground accuracy of about 0.65 meters, which is well beyond the
accuracy of the NOAA/NGS 1:5,000 scale T-Sheets and the
USGS 1:24,000 scale topographic maps. Shorelines thus derived
can be used in a variety of coastal applications.
ACKNOWLEDGEMENTS
This research is supported by the Digital Government Program of
the U.S. National Science Foundation.
694
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