INTEGRATING LIDAR AND HIGH-RESOLUTION IMAGERY DATA FOR
TOPOGRAPHIC AND HYDROLOGICAL MAPPING OVER A COASTAL MARSH AREA
X.
Yang
Florida State
University, Department of Geography, Tallahassee, Florida,
USA
xyang@fsu.edu
Because of their great environmental and
ecological values, coastal marshes have been targeted in numerous
interdisciplinary efforts that aim to discover patterns, relationships, and
models leading to successful management and sustainable use of the resources.
However, these efforts may be hindered because of the lack of adequate
topographical data over coastal tidal areas.
Most of the currently available digital elevation data sets, such as
GTOPO30, USGS DEMs, and NASA SRTM, are basically useless for coastal marsh
areas where the terrain is featureless and of limited contrast. Thus, there is a strong need to develop
high-resolution topographic data sets for these environmentally sensitive
areas. This article reports a research effort that aims to investigate the
utility of integrating lidar and high-resolution imagery data for topographic
and hydrological mapping with part of the North Inlet bay in Georgetown, South Carolina,
USA as a
case. The study site is largely below 1
meter above the sea level, consisting of salt marshes behind barrier islands,
scattered with numerous tidal creeks. The lidar data were collected in January
2003 and the entire data set was processed by using vegetation removal
algorithms to create a bare-earth model.
The nominal posting density ranges from 1.5 to 5 meters. A triangulated
irregular networks (TIN) model was derived from the lidar data through the
Delaunay triangulation. The TIN model
was further converted into a grid-based surface model with 1-meter cell size. Then, accuracy assessment was conducted by
using a random sample of 1024 points through a cross-validation method. The model was found to have a global RMSE of
0.05 meter, indicating very high vertical accuracy. With this grid-based digital terrain model,
hydrographical features were further extracted by using GIS-based hydrological
modeling, which were validated by using a high-resolution ADAR (Airborne Data
Acquisition and Registration) image covering the same area that was acquired in
October 2000. It is found that the
stream networks extracted from the lidar-derived digital terrain model match
the tidal creeks protracted from the ADAR image with 0.7-m spatial resolution
quite well. This study demonstrates that lidar data are particularly suitable
for topographic and hydrological mapping over low-lying areas but cautions
should be paid upon the choice of threshold values in the GIS-based
hydrological network modeling.