SPATIO−TEMPORAL ANALYSIS OF BEACH MORPHOLOGY USING LIDAR, RTK−
GPS AND OPEN SOURCE GRASS GIS
Helena Mitasova,1,2 David Bernstein,3 Thomas G. Drake,1 Russell Harmon,2 Carl Miller, Jessie
McNinch
Abstract: Open source software is gaining attention as a viable alternative to proprietary
systems, especially by providing the freedom do run, study, distribute and improve/modify the
code. We have explored the suitability of the GRASS GIS for coastal studies and implemented
enhancements that improve the efficiency and flexibility of spatial interpolation and surface
analysis specifically for coastal topography and bathymetry measurements. Mapping
technologies used for coastal studies such as LIDAR and RTK−GPS produce massive amounts
of data characterized by oversampling and noise. The physical phenomena and landscape
changes examined are often subtle and besides statistical accuracy, adequate representation of
surface geometry is crucial for correct interpretation of measured data. In this work, we have
utilized a robust, accurate and flexible spatial interpolation method based on splines. Surface
gradient and curvatures, needed for topographic analysis and simulation of processes were
computed simultaneously with interpolation. Raster map algebra was used for data management
(masking, extraction of subsets) as well as for spatio−temporal analysis, such as computation of
first and second order differences between surfaces. Visualization of multiple 3d surfaces with
moving cutting planes provided powerful tools for visual identification of features and changes.
INTRODUCTION
Coastal topography is a result of complex interactions between anthropogenic activities and
natural processes. Quantification of short−term spatial change in this dynamic environment is
crucial for sustainable coastal management. Traditional monitoring methods have relied on
survey transects and aerial photography. Both approaches are rather time consuming and require
substantial manual processing. Modern mapping technologies such as laser altimetry (LIDAR),
Real Time Kinematic GPS (RTK−GPS), digital photogrammetry, interferometric sonar and
multispectral imagery greatly enhance the capabilities to gather georeferenced data at
unprecedented spatial and temporal resolutions. The efficiency of these highly automated
technologies enables repeated surveys in relatively short time intervals, creating time series of
elevation data that provide critical information for areas with highly dynamic topography typical
for coastal regions. For example, LIDAR has been used for regular mapping of the coastal
change since 1996 (NOAA−USGS 2002). RTK GPS is being increasingly applied to cost
effective, rapid beach monitoring (Morton et al., 1999; Freeman, et al. 2003; Bernstein, 2003).
However, there are still challenges in using the full potential of this new type of data for
important applications such as disaster prevention and management, homeland security and
sustainable development. The problems are usually related to the fact that the data sets are
several orders of magnitudes larger than what the current GIS tools were designed for, and they
have substantially different spatial distribution and properties than data acquired by traditional
methods. Recent developments of modular and extendable proprietary GIS tools as well as
emergence of Open Source GIS (Neteler and Mitasova, 2002) have created an opportunity to
extend the range of GIS applications to new areas and new types of data, including
1)Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695, email:
hmitaso@unity.ncsu.edu
2) Army Research Office, Army Research Laboratory, Research Triangle Park, NC 27709, Harmon@aro.arl.army.mil
3) Center For Marine and Wetland Studies, Coastal Carolina University, Conway, SC 29526, email: dbernste@coastal.edu

oceanography and coastal studies. Advanced 3D systems substantially increase efficiency in data
processing and provide the tools to gain new insights into geospatial aspects of complex coastal
systems. GIS is beginning to play an important role in a wide range of applications, such as
monitoring, analysis and risk assessment, prediction of impacts using modeling and simulations,
and planning and decision support (NOAA 2000; Wright and Bartlett 1999). In this paper, we
focus on methods for assessment of rapid changes in coastal topography and on the capabilities
of Open source GRASS 5.0 GIS to support processing and analysis of new type of data from the
monitoring programs.
METHODS
The methodology for monitoring and analysis of recent beach morphology evolution was
developed for a beach nourishment site on the Bald Head Island which belongs to the system of
North Carolina’s barrier islands (Figure 1). This South Beach site is located near the mouth of
the Cape Fear river and displays complex interactions between anthropogenic activities and
natural processes. Analysis of historical maps (Cleary et al. 1989) has shown rotation of its
shoreline around relatively stable pivot point area. The counter−clockwise rotation accompanied
by growth of the west section of the South Beach (over 800m), observed during the period 1850
− 1962 was reversed in late 60ies when Wilmington harbor channel was deepened to 12m and in
some places reached the rock (Cleary et al., 1989). In spite of relatively restricted development,
beach erosion, especially in areas close to the channel, has become an increasing problem
requiring recent intervention.
To obtain new insights into the response of this beach to ongoing anthropogenic activities
bathymetry and coastal elevation data from diverse sources were integrated and analyzed within
GIS. Specifically, terrestrial LIDAR and RTK−GPS data have been combined with offshore
single beam and interferometric sonar soundings to create an integrated model of bathymetry
and beach topography (Figure 1) and its evolution in response to recent US Army Corps of
Engineers beach renourishment, canal dredging, and storage of dredged materials in underwater
mounds (see more information about the projects and monitoring programs at FRF 2002). The
developed methodology involves data acquisition, preprocessing (including georeferencing,
projection and rectification typically performed within a surveying system), data import into
GRASS GIS and transformation to a common raster data model, and finally, spatial and spatio−
temporal analysis and visualization. In this paper we focus on the pre and post nourishment
evolution of the South Beach subaerial topography.

Topographic surveys.
Pre−nourishment shoreline and beach evolution was analyzed using LIDAR data acquired
during the Airborne LIDAR Assessment of Coastal Erosion (ALACE) project. The ALACE
project was a partnership between the NOAA Coastal Services Center, the NASA Observational
Sciences Branch, and the U.S. Geological Survey (USGS) Center for Coastal Geology. The
partnership collected LIDAR data along the sandy beaches of the U.S. from September 1996 to
October 2000 using the NASA Airborne Topographic Mapper (ATM) sensor. Technical details
about the surveys and the equipment can be found on the project’s web site (NOAA−USGS
2002 ). The data for the study area were available for the years 1997, 98, 99 and 2000. They
were downloaded using LIDAR Data Retrieval Tool (LDART 2002) as point clouds x,y,z in
State Plane coordinate system in meters. While it was possible to download data as gridded (or
Mitasova et al
2