January 13, 2004
14:38
WSPC/101-CEJ
00092
Recent Developments in the Geomorphic Investigation
595
Table 3. Typical spectral features of high-resolution
commercial satellite imagery.
Spectral Region
Spectral Range in
Image Spatial
Microns
Resolution
Panchromatic
0.450.90
1 meter
Band 1 (blue)
0.450.52
Approximately
Band 2 (green)
0.510.60
4-meter
Band 3 (red)
0.630.70
multispectral
Band 4 (near IR)
0.760.85
major features of commercially available satellite imagery in the optical part of the
spectrum where remote sensing data can be applied to coastal studies. The repeat
cycle for a particular geographic location depends on the latitude, but generally the
mid-latitudes are revisited every 3 to 8 days.
Generally commercial satellite imagery can be acquired in GIS-ready format in-
cluding georeferencing to either local or UTM coordinate systems. The spatial res-
olution in the panchromatic band is on the order of 1 meter, whereas the resolution
in 4-band multispectral images is on the order of 4 meters (Table 3). Although the
excellent temporal and spatial resolution of currently available commercial satellite
data would facilitate application to shoreline change and geomorphic analysis this
application is still under development. Due to relatively low cost and high temporal
resolution satellite imagery may eventually replace aerial photography as the main
tool for coastal change analysis.
Among the many possible uses of satellite remote imagery, bathymetric data
acquisition holds promise for having a significant advantage in cost and resolution
in coastal regions having relatively clear water. Algorithms for extracting depth from
multispectral imagery have already been tested to a limited extent (Lyzenga, 1978;
Stumpf and Holderied, 2003).
Standard algorithms for determining depth in clear water from passive mul-
tispectral remote sensors where sensors already exist, but require several tuning
parameters (Stumpf and Holderied, 2003). In additional, existing algorithms have
difficulty in retrieving depths where the bottom has an extremely low albedo. In on-
going work to develop practical depth extraction from shallow marine environments,
empirical solutions, having fewer tunable parameters, could be applied to a larger
range of albedo features using spectral reflectance bands of high resolution satellite
imagery. The two algorithms, a standard linear transform, and a ratio transform will
be compared using IKONOS satellite imagery and LIDAR bathymetry from Palm
Beach County, Florida. Stumpf and Holderied (2003) used this approach for ex-
tracting depth in shallow coral reef environments. To date, however spectral remote
sensing methods for depth extraction have not been adapted to coastal zones hav-
ing sediment constructed beach and nearshore profiles. In the near future, however,
algorithms based on combinations of three visible and one infrared band of the
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