• LIDAR Data Availability
• Viewing LIDAR Data in a GIS
• Using LIDAR Data to Build GIS Data Layers

LIDAR Data Availability

Figure 4.2. A map showing areas for which LIDAR coverages exist

The first step in using LIDAR data is to determine if data are available for your area of interest.  The best way to accomplish this is to check the National Oceanic and Atmospheric Administration (NOAA) Coastal Services Center web page at /crs/beachmap . The next step is to download the data.  Researchers at the Center have developed a web-based software application, for accessing the LIDAR data. Using the LIDAR DAta Retrieval Tool (LDART) to extract data, LIDAR data sets are delivered via the web as comma delimited text files that can be uploaded into a geographic information system (GIS). For step-by-step instructions on how to access LIDAR data from LDART and how to process the data using ArcView® GIS, the following tutorials can be used:

Using LIDAR Data in an ArcView® Project
This section provides information and instructions for acquiring and loading LIDAR data into an ArcView project.

Creating Grids, Contours, and Hillshades in ArcView Spatial Analyst®
This section describes how to create grids, contours and hillshades in ArcView using the Spatial Analyst Extension.  NOTE: Spatial Analyst is an add-on extension that can be purchased for use with ArcView. 

Viewing LIDAR Data in a GIS

Once the data are obtained, loaded, and processed, they can be viewed in several different formats. Viewing LIDAR beach elevation data in its native point or x,y,z format (Figure 4.3) allows a user to understand the density and spatial distributions of the data.  In remote sensing, color coded images are common. They serve as an effective means for visualizing data.  Because the data are so dense, the surface almost looks continuous.  In addition, examining LIDAR beach elevation data in its native point or x,y,z format allows a user to understand the distribution of the data horizontally as well as vertically. Because each individual point is a discrete geographic entity, point display may have gaps in data coverage.
 

Figure 4.3. Point Display of LIDAR data - Northern End of  Wrightsville Beach, N.C.

Another way of displaying elevation data is in a grid format (Figure 4.4). In this format, each cell is assigned a value based on surrounding elevation points. This gives the data a continuous distribution resulting in a smooth surface when displayed. Figure 4.4 is a color-coded grid of the northern end of Wrightsville Beach, North Carolina, gridded at a five-foot resolution. Once the LIDAR data are in a grid format, other products such as Digital Elevation Models (DEM), and contour and shaded relief maps can be created. Displaying the data as a DEM allows for a high resolution color enhanced display of the LIDAR data.  The legend in Figure 4.4 has a range of numbers from -4 feet to 25+ feet. These numbers indicate the relationship between the colors on the legend and the actual elevations depicted on the map. For example, in the image of Wrightsville Beach, the blue colors represent elevations near sea level, whereas the darker red colors indicate higher elevations such as high sand dunes, houses, and buildings. Grid data can provide detailed information about volumetric and surface changes on a beach. LIDAR data can be useful information in analyzing sediment movement after a renourishment project or a major storm event.
 

Figure 4.4. Grid Display of LIDAR data - North End of Wrightsville Beach (original grid size = 5ft)

Contour lines are another way of displaying LIDAR data (Figure 4.5).  Contours are lines of constant elevation with a specified interval.  They provide an effective way of showing gradient change. The closer the contour lines are to each other, the steeper the beach face. Conversely, the further the contour lines are from each other, the flatter the beach face. Contour maps can be used to show elevation along a continuous line. For example, if you are interested in finding the four-foot elevation line as a baseline to determine a construction setback, the four-foot continuous line of elevation can be selected from a contour file in a GIS as shown below.

Figure 4.5. Contours of the Northern End of Wrightsville Beach

Another effective way of visualizing LIDAR data is by hillshading (Figure 4.6).  Hillshading creates a shaded relief map from a grid.  Using an imaginary light source at a specified altitude and direction, a shadow is cast creating the perception of a 3-dimensional surface. Shaded relief maps provide a good way to interpret features on a beach.  For example, escarpments, groins, docks, and sand dunes can be interpreted easily from these maps.

Figure 4.6. Shaded Relief of the Northern End of Wrightsville Beach

To see samples of  LIDAR grids, contour maps, and shaded relief maps for all of the islands in New Hanover County, click on the area of your choice in the table below.

Using LIDAR Data to Build GIS Data Layers

Figure 4.7. 1994 Building footprint overlain on a 1997 LIDAR-based shaded relief map.

LIDAR data also provide the potential for GIS data development. Some examples of GIS data that could be derived from LIDAR data are building footprints, piers, groins, docks, and jetties.  Docks, for example, could be digitized and attributed from a LIDAR-based shaded relief map. Current LIDAR data also provide a good opportunity to update databases such as those for building footprints.  The image shown here, (Figure 4.7), is a 1997 LIDAR-based shaded relief map with a 1994 building footprint overlay.  Circled in red are houses that existed during the county-wide building inventory in 1994. A 1997 LIDAR-based shaded relief map shows that these structures no longer exist. Based on the information, the building footprint database can be updated. With current LIDAR data, an up-to-date structure inventory can be performed.